JP7206581B2 - Velocity-based control in aperiodically updated controllers, methods for controlling processes, process controllers - Google Patents

Description

This patent relates to methods and system compensation for providing velocity-based control in process control systems using aperiodic control or slow feedback process variable communication, and more particularly to process dynamics and comparison. Devices and methods configured to robustly control a process when implementing control when receiving process variable feedback at a slow rate.

Process control systems, such as distributed or scalable process control systems such as those used in chemical, petroleum, or other processes, typically communicate via analog, digital, or combined analog and digital buses. includes one or more process controllers communicatively coupled to each other, to at least one host or operator workstation, and to one or more field devices. Field devices, which can be, for example, valves, valve positioners, switches, and transmitters (e.g., temperature, pressure, and flow sensors), perform functions within a process such as opening or closing valves and measuring process parameters. I do. The process controller receives signals indicative of process measurements made by the field device and/or other information about the field device and uses this information to implement control routines to generate control signals and to control the control. Signals are sent over the bus to field devices to control the operation of the process. Information from field devices and controllers is typically available to one or more applications executed by operator workstations. It allows the operator to perform any desired function on the process, such as verifying the current state of the process, modifying the operation of the process, and the like.

Some process control systems, such as the DeltaV® system sold by Emerson Process Management, use functional blocks or groups of functional blocks called modules located in controllers or different field devices to perform control and/or monitoring operations; In these instances, the controller or other device may contain and execute one or more functional blocks or modules, each of which is associated with another functional block (either within the same device or within a different device). and/or provide output to other functional blocks such as measuring or sensing process parameters, monitoring devices, controlling devices, or performing proportional-integral-derivative (PID) control routines. Take some process action, such as performing a control action. Different functional blocks and modules within a process control system are generally configured to communicate with each other (eg, via a bus) to form one or more process control loops.

A process controller typically implements a different algorithm, subroutine, for each of a number of different loops defined with respect to the process or contained within the process, such as flow control loops, temperature control loops, pressure control loops, etc. , or programmed to execute control loops (which are all control routines). Generally speaking, each such control loop controls one or more input blocks, such as analog input (AI) function blocks, or a single output, such as proportional-integral-derivative (PID) or fuzzy logic control blocks. and output blocks such as analog output (AO) function blocks. Control routines, and the functional blocks implementing such routines, are configured according to a number of control techniques, including PID control, fuzzy logic control, and model-based techniques such as Smith Predictor or Model Predictive Control (MPC). there is

To support the execution of routines, a typical industrial or process plant has a centralized control room communicatively connected to one or more process controllers and process I/O subsystems. The I/O subsystem is connected to one or more field devices. Traditionally, analog field devices are connected to controllers by two- or four-wire current loops for both signal transmission and power delivery. Analog field devices (eg, sensors or transmitters) that transmit signals to the control room modulate the current through the current loop such that the current is proportional to the sensed process variable. On the other hand, analog field devices that act under the control of the control room are controlled by the magnitude of the current through the loop.

With the increasing amount of data transfer, one particularly important aspect of process control system design is how field devices are communicatively coupled to each other, to controllers within the process control system or process plant, and to other systems or devices. Including the form to be used. Generally, the various communication channels, links, and pathways that allow field devices to function within a process control system are commonly collectively referred to as an input/output (I/O) communication network. .

The communications network topology and physical connections or paths used to implement the I/O communications network are critical to the robustness or integrity of field device communications, especially when the network is subjected to adverse environmental factors or severe conditions. can have a significant impact. These factors and conditions can compromise the integrity of communications between one or more field devices, controllers, and the like. Communication between controllers and field devices is particularly sensitive to any such disruption, as monitoring applications or control routines typically require periodic updates of process variables for each iteration of the routine. be. Impaired control communications can therefore result in reduced efficiency and/or profitability of the process control system and excessive wear or damage to equipment, as well as any number of potentially harmful failures.

To ensure robust communication, I/O communication networks used in process control systems have historically been hardwired. Unfortunately, hardwired networks introduce numerous complications, challenges, and limitations. For example, the quality of hardwired networks can degrade over time. Further, hardwired I/O communication networks, especially when the I/O communication networks are associated with large industrial plants or facilities distributed over large areas, such as refineries or chemical plants that consume several acres of land. are typically expensive to install. The long wiring installations required typically involve significant labor, materials, and expense, and can introduce signal degradation resulting from wiring impedance and electromagnetic interference. For these and other reasons, hardwired I/O communication networks are generally difficult to reconfigure, modify, or update.

It has been proposed to use wireless I/O communication networks to alleviate some of the problems associated with hardwired I/O communication networks. For example, U.S. Patent Application Publication No. 2003/0043052, entitled "Apparatus for Providing Redundant Wireless Access to Field Devices in a Distributed Control System," the entire disclosure of which is expressly incorporated herein by reference, is a hardwired communication Disclosed is a system that utilizes wireless communication to augment or supplement the use of.

Reliance on wireless communication for control-related transmissions has traditionally been limited due to reliability concerns, among other things. As explained above, modern monitoring applications and process control rely on reliable data communication between controllers and field devices to achieve optimum levels of control. Additionally, typical controllers execute control algorithms at high speeds to quickly correct undesirable deviations in the process. Undesirable environmental factors or other adverse conditions may produce intermittent interference that impedes or prevents the high speed communications necessary to support such execution of monitoring and control algorithms. Fortunately, wireless networks have become much more robust over the past two decades, allowing reliable use of wireless communications in several types of process control systems.

However, power consumption remains a complicating factor when using wireless communications in process control applications. Because wireless field devices are physically separated from the I/O network, field devices typically need to provide their own power source. Thus, field devices can be battery powered, draw solar energy, or draw environmental energy such as vibration, heat, pressure, and the like. For these devices, the energy consumed for data transmission can be a significant portion of the total energy consumption. In fact, more during the process of establishing and maintaining a wireless communication connection than during other critical operations performed by the field device, such as the steps taken to sense or detect the process variable being measured. May consume a lot of power. Implementing a wireless process control system in which field devices, such as sensors, communicate with the controller in an aperiodic, slow, or intermittent fashion to reduce power consumption of the wireless process control system and thus extend battery life has been proposed to do. In one instance, a field device may communicate with or transmit process variable measurements to a controller only when a significant change in the process variable is detected, leading to aperiodic communication with the controller. can.

One control technique that has been developed to handle aperiodic process variable measurement updates is the expected process response to control signals generated by the controller during infrequent or aperiodic measurement updates. Use a control system to provide and maintain instructions for The expected process response can be developed by a mathematical model that calculates the expected process response to control signals for a given measurement update. An example of this technique is described in US Pat. No. 7,587,252, entitled "Non-Periodic Control Communications in Wireless and Other Process Control Systems," the entire disclosure of which is expressly incorporated herein by reference. ing. Specifically, this patent generates an indication of the expected process response to a control signal upon receipt of an aperiodic process variable measurement update and waits until the arrival of the next aperiodic process variable measurement update. , discloses a control system having a filter that maintains a generated indication of expected process response. As another example, U.S. Pat. No. 7,620,460, entitled "Process Control With Unreliable Communications," the disclosure of which is expressly incorporated herein by reference in its entirety, describes an expected response to a control signal. but includes a filter that further modifies the filter to incorporate measurements of the time elapsed since the last aperiodic measurement update to produce a more accurate indication of the expected process response. , disclose the system.

However, in many control applications, the process control system may receive setpoint changes during process operation. In general, a proportional action on the error between the setpoint and the measured process variable when the setpoint changes during the execution of a periodically updated control system (e.g. hardwired control communication system) A controller designed to do will change the controller output immediately to drive the process variable towards the new steady state value. However, in a wireless control system receiving infrequent, aperiodic measurement updates, operating as described in both examples above, the measured process response reflected by each new measurement update is , reflects changes made in the controller output that are captured for the last measurement update, in addition to changes in the output caused by setpoint changes that occur some time after the last measurement update is received. In this case, calculating the controller reset component based on the controller output (as described in U.S. Pat. No. 7,620,460) and the time since the last measurement update is the last measurement It may overcompensate for changes that occur after an update. Therefore, the process response to setpoint changes may differ based on when the setpoint change occurred after the last measurement update. As a result, the system continues to rely on previously generated (and now outdated) expected response indications when the controller generates the control signal after a setpoint change, so does not respond quickly or robustly to To solve this problem, US Patent Application Publication No. 2013/0184837, entitled "Compensating for Setpoint Changes in a Non-Periodically Updated Controller," the disclosure of which is expressly incorporated by reference in its entirety, addresses any new process variable Using a continuously updated filter in a feedback loop within the controller to track the behavior of the controlled variable during times when no measurements are received and when new process variable measurements are received at the controller A system is disclosed that sometimes uses the output of this controller, but otherwise uses the output of a filter from the most recent time a process variable measurement was received to generate a control signal. . In this system, the generated control signal responds better and performs better when the process variable set point changes during the time the process variable measurement is received.

Additionally, when using battery-powered transmitters in wireless control systems, it is desirable to set up the system to maintain long battery life. For example, obtaining a battery life of 3-5 years using current transmitter and battery technology generally requires the use of communication update rates of 8 seconds or greater. However, in order to maintain control of the process, it is important to still have process feedback measurements received at a rate that is at least four times the rate associated with the process response time (i.e., the inverse of the process response time). Therefore, using such a slow update rate limits the use of PID (proportional-integral-derivative) based radio control to processes with process response times of 30 seconds or more.

Still further, wireless control, including those using generating a position output, such as a 4-20 ma signal or a digital signal, provided to a valve or other controlled element that indicates the final position to be moved. There are various types of PID algorithms that can be used to address. However, a velocity-based control signal directing a valve or other controlled element to move a particular amount in a particular direction, e.g., by energizing the movable element for a particular amount of time. There are also other PID algorithms that provide. Such velocity-based control signals are commonly used with electric motors and are modulated to indicate the amount of time a valve must be energized in order to move it for a specified period of time. A control signal is provided in the form of a pulse signal (having a pulse width of Velocity-based controllers tend to produce changes in the position signal rather than signals indicative of the actual position obtained by the moveable element. Therefore, velocity-based control algorithms tend to be used to provide incremental (increase/decrease) output to actuators, and thus can be used in controlling actuators that are incapable of providing position feedback. can.

Control techniques enable robust control of processes or control loops that have fast dynamics with respect to the rate at which measurements of the controlled process variables are provided as feedback to the process controller. Specifically, the present control techniques may use PID algorithms in the form of position or velocity to control the process, where the measured value of the process variable or feedback signal equals the process response time or even provided to the controller at longer time intervals. Specifically, the control technique can be used to provide robust control in processes with response times that are two to four times shorter than the feedback time interval. Such situations may occur, for example, when feedback measurements of process variables are sent to the controller wirelessly, intermittently, or at time intervals shorter than, close to, or longer than the response time of the process. This can occur when using the radio control provided.

The disclosed velocity PID control routine is useful for actuators requiring position or incremental inputs to control using wireless measurements when the actuators require incremental inputs and no position feedback is available to the controller. and to address legacy installations as well as new installations where wireless measurements are used for control. can be done. Additionally, adjustments to the PID algorithm in the form of speed can be made based on process gains and dynamics and are independent of wireless communication rate. Still further, the PID control routine in the form of velocity automatically holds the last output position upon loss of communication and provides bumpless recovery when communication is re-established.

In one instance, controllers implementing new control techniques generally include different structures in which differential, proportional, integral, and derivative control signal components are generated and used to provide differential or moving control signal components. which is then sent to a controlled device, eg a valve, to control the operation of the controlled device and thus the process. This difference or speed-based form of control produces a control signal that performs better than standard PID control in the presence of slow process variable feedback measurements. Specifically, a controller using this control technique generates a differential proportional value representing the difference between the previous proportional control signal component and the newly calculated proportional control signal component during each controller iteration. and the proportional value of this difference is used as the basis for each new control signal from the controller. However, various other control signal components, such as a derivative control signal component and/or an integral control signal component, can be added to the differential proportional control signal component when new process variable measurement signals are available at the controller. , or in combination with said components. These two control signal components can also be based on the difference between the newly calculated value and the previously calculated value. Specifically, new derivative components can be calculated during controller iterations, at which time newly received values of process variable measurements can be utilized by the controller. Similarly, new integral components can be generated using a continuously updated filter that generates a new indication of the expected response of the process to each iteration of the controller's control routine. However, the continuously updated filter output is used to generate new integral elements only when new values of process variable measurements are received. Otherwise, the integral control signal component is set to zero.

The speed-based PID control technique disclosed herein uses a differential form to rapidly respond to setpoint changes (even during the time the process variable feedback signal is present at the input of the controller). Generates a suitable control signal but is still slower than the inverse of the response time of the process being controlled (e.g., 2-4 times slower), close to the inverse of the response time, or the inverse of the response time. It provides robust and stable control in the presence of slowly received (eg, intermittent) feedback signals, including feedback signals received at a faster rate.

1 is a block diagram of an exemplary periodically updated hardwired process control system; FIG. 4 is a graph illustrating process output response to process input of an exemplary periodically updated hardwired process control system, including process response time; 1 is a block diagram illustrating an example of a wireless process control system having a controller that receives slow or aperiodic feedback inputs; FIG. 1 is a block diagram of an exemplary controller that enables robust compensation of setpoint changes or feedforward disturbances in a periodically updated hardwired process control system; FIG. 4B is a graph illustrating the process output response of the example controller of FIG. 4A as the controller responds to several setpoint changes; 1 is a block diagram of an exemplary controller for compensating for setpoint changes in an aperiodically updated process control system, where the controller compensates for process and/or measurement delays in feedback signals. FIG. 1 is a block diagram of an exemplary controller for compensating for setpoint changes in an aperiodically updated process control system in which the process controller uses differential contribution or rate contribution to determine the control signal; FIG. Aperiodically updated process control in which the process controller receives additional controller input data provided from field devices, control elements, or other downstream devices to affect the operational response of the process FIG. 4 is a block diagram of an exemplary controller that provides compensation for setpoint changes in a system; 1 is a block diagram of an exemplary controller for compensating for setpoint changes in an aperiodically updated process control system in which the process controller adapts to the use of either actual or implicit controller input data to field devices; FIG. FIG. 4 is a block diagram of an exemplary velocity-based PI controller that enables robust compensation of setpoint changes or feedforward disturbances in a process control system in response to slowly received process variable measurement signals. FIG. 4 is a block diagram of an exemplary velocity-based PID controller that enables robust compensation of setpoint changes or feedforward disturbances in a process control system in response to slowly received process variable measurement signals. 4 is a graph illustrating the simulated process response of an exemplary prior art speed-based PID controller in both wired and wireless configurations in response to a setpoint change in the primary control variable and having a process response time of 8 seconds; be. 4 is a graph illustrating the simulated process response of an exemplary rate-based PID controller according to the present invention in both wired and wireless configurations in response to a setpoint change in the primary control variable and having a process response time of 8 seconds; be. 4 is a graph illustrating the simulated process response of an exemplary prior art speed-based PID controller in both wired and wireless configurations in response to a setpoint change in the primary control variable and having a process response time of 3 seconds; be. 4 is a graph illustrating the simulated process response of an exemplary rate-based PID controller according to the present invention in both wired and wireless configurations in response to a setpoint change in the primary control variable and having a process response time of 3 seconds; be. FIG. 4 is a graph illustrating simulated process response of an exemplary prior art speed-based PID controller in both wired and wireless configurations in response to disturbance changes and having a process response time of 8 seconds; Fig. 10 is a graph illustrating the simulated process response of an exemplary inventive rate-based PID controller in both wired and wireless configurations in response to disturbance changes and having a process response time of 8 seconds; FIG. 5 is a graph illustrating simulated process response of an exemplary prior art speed-based PID controller in both wired and wireless configurations in response to disturbance changes and having a process response time of 3 seconds; Fig. 10 is a graph illustrating the simulated process response of an exemplary inventive rate-based PID controller in both wired and wireless configurations in response to disturbance changes and having a process response time of 3 seconds;

Control techniques can be used to provide control in process loops in which the process measurement feedback signal is received slowly or intermittently, and in particular, the process measurement feedback signal can be used to control the process measurement feedback signal, such as the inverse of the process response time. It is useful when receiving at a rate that is slower than, similar to, or slightly faster than the rate associated with the process dynamics involved. The controller, e.g., in a slow and/or aperiodic manner, particularly below the process response rate of the process dynamics being controlled (i.e., the reciprocal of the process response time to the process variable being controlled). It can be used in a controller that receives a process measurement signal as a feedback signal at a rate comparable to or otherwise similar to the process response rate. In one instance, the control technique combines a proportional contribution signal with one or more of a differential contribution signal and an integral contribution signal to generate a control signal for use in controlling a process device such as a valve. . In one instance where a velocity-based PID algorithm is used, the controller generates a proportional contribution value from the difference between the setpoint and the feedback signal of the most recently received process variable measurement. This error signal is then provided to a difference unit which multiplies the gain signal to determine the change in this signal since the last execution cycle of the controller. Further, the differentiating unit receives the error signal and basically differentiates the error signal over time since the last measurement signal was received by the controller so that the differential calculation can be performed on the error signal. The output of the derivative module or calculation is also provided to a change detection unit or difference unit to determine the difference between the current output of the derivative calculation and the previous value used to calculate the control signal. Similarly, an integral computation unit receives and integrates (eg, sums) the difference in the control signal as a product of the proportional unit and the derivative unit. The output of the adder is provided to a filter for filtering the output of the adder to produce an integrated contribution signal. However, this integral contribution is provided to an adder which only sums this contribution with the output of the control signal when a new feedback value is provided to the controller. That is, the integral contribution is set to zero for all controller iterations, except those for which a new feedback signal is available at the controller.

Generally speaking, the continuously updated filter of the integral contribution unit in the controller ensures that each control routine iteration of the controller, despite slow or aperiodic reception of process variable measurement updates from field devices, , an indication of the expected process response (also called feedback contribution) is generated. A continuously updated filter was generated previously from the last control routine iteration and control routine execution period, in part, to generate an indication of the expected response during each control routine iteration. Use expected response indications. Additionally, an integral output switch in the controller provides the continuously updated output of the filter to the control signal as a feedback contribution, such as an integral (also known as reset) contribution based on the indication of the most recent measurement. . Generally speaking, the integral output switch outputs the last measured value update in the PID controller in the form of velocity as an integral or reset contribution to the control signal during each iteration of the controller where no new measured value signal is available. is received by the controller, providing the expected process response as produced by a continuously updated filter, or a zero value. When a new measurement update is available, the integral output switch responds to a new indication of the expected process response generated by the continuously updated filter (based on the new measurement update indication). Clamp and provide the new expected process response as the integral contribution of the control signal. As a result, the controller uses a continuously updated filter to determine a new expected response of the process during each controller iteration, each new expected process response resulting in a new measurement at the controller. Even if the integral or reset component of the control signal changes only when it is available, it is done in the time between measurement updates, and the controller output changes during development of the control signal. Reflects the effect of setpoint changes or feedforward changes that have an impact.

FIG. 1 illustrates a process control system 10 that can be used to implement the control methods described. The process control system 10 can be connected to a data historian 12 and to one or more host workstations or computers 13 (which can be any type of personal computer, workstation, etc.), each of which: It includes a process controller 11 having a display screen 14 . Controller 11 is also connected to field devices 15 - 22 via input/output (I/O) cards 26 and 28 . Data historian 12 may be any desired type of data acquisition unit having any desired type of memory for storing data and any desired or known software, hardware, or firmware. can be done. In FIG. 1, controller 11 is communicatively connected to field devices 15-22 using a hardwired communication network and communication scheme.

In general, field devices 15-22 can be any type of device such as sensors, valves, transmitters, positioners, etc., while I/O cards 26 and 28 can be any desired communication device. or any type of I/O device that conforms to the controller protocol. Controller 11 includes processor 23 that implements or directs one or more process control routines (or any module, block, or subroutine thereof) stored in memory 24 . Generally speaking, controller 11 communicates with devices 15-22, host computer 13, and data historian 12 to control the process in any desired manner. In addition, controller 11 implements control strategies or schemes using what are commonly referred to as function blocks, each function block (links and An object or other part (eg, subroutine) of the overall control routine that operates with other functional blocks (via communication called). Functional blocks are typically input functions, PIDs, fuzzy logic controls such as those associated with transmitters, sensors, or other process parameter measurement devices to perform some physical function within the process control system 10. or an output function that controls the operation of some device such as a valve. Of course hybrids and other types of functional blocks exist and can be utilized herein. Functional blocks may be stored in and executed by controller 11 or other devices, as described below.

As illustrated in decomposition block 30 of FIG. 1, controller 11 may include several single-loop control routines, illustrated as control routines 32 and 34, and if desired, control loop One or more advanced control loops, illustrated as 36, may be implemented. Each control loop is typically referred to as a control module. The single-loop control routines 32 and 34 have suitable analog inputs (e.g., AI) and analog output (AO) function blocks, respectively, using a single-input/single-output fuzzy logic control block and a single-input/single-output PID control block to provide single-loop control. exemplified. The advanced control loop 36 is illustrated as including an advanced control block 38 having inputs communicatively connected to one or more AI function blocks and outputs communicatively connected to one or more AO function blocks. However, the inputs and outputs of advanced control block 38 may be connected to any other desired functional blocks or control elements to receive other types of inputs and to provide other types of control outputs. can be done. The advanced control block 38 can implement any type of multiple-input, multiple-output control scheme and also includes model predictive control (MPC) blocks, neural network modeling or control blocks, multivariable fuzzy logic control blocks, real-time optimizers. It can constitute or contain blocks and the like. The functional blocks illustrated in FIG. 1, including advanced control block 38, can be executed by stand-alone controller 11, or alternatively, by one of workstations 13 or one of field devices 19-22. It will be appreciated that it may be located and executed within any other processing device or control element of a process control system, such as one. As an example, field devices 21 and 22 may be transmitters and valves, respectively, and may execute control elements for implementing control routines, and thus may be one or more functional blocks, such as , processing components and other components for implementing portions of the control routines. More specifically, as illustrated in FIG. 1, field device 21 may have memory 39A for storing logic and data associated with analog input blocks, while field device 22 may: An actuator may be included with memory 39B for storing logic and data associated with PIDs or other control blocks in communication with the analog output (AO) block.

The graph of FIG. 2 generally illustrates control loops 32, 34, and 36 (and/or any control loop incorporating functional blocks present in field devices 21 and 22 or other devices). 4 illustrates process outputs deployed in response to process inputs of a process control system, according to one or more implementations. The control routine being implemented generally executes in a cyclical fashion through a number of controller iterations, with the number of control routine executions indicated along the time axis by heavy arrows 40 in FIG. In the conventional case, each control routine iteration 40 is supported by updated process measurements indicated by thin arrows 42 provided, for example, by a transmitter or other field device. As illustrated in FIG. 2, there are typically multiple periodic process measurements 42 made and received by the control routine during each periodic control routine execution time 40 . To avoid the limitations associated with synchronizing measurements with control execution, many known process control systems (or control loops) attempt to oversample process variable measurements by a factor of 2-10. designed to Such oversampling helps ensure that the process variable measurements for use in the control scheme are up to date during each control routine execution or iteration. Also, to minimize control variability, conventional designs suggest that feedback-based control should run 4 to 10 times faster than the process response time, and that new process variable measurements are sent to each controller. It is defined that it can be used repeatedly. The process response time is the process time constant (τ) (e.g., 63% of the change in process variable) plus the process delay or dead time (T _D ) after making a step change 44 in the process input (T D ) (bottom of FIG. 2). 2, as represented by the process output response curve 43 of the graph of FIG. In any event, to meet these conventional design requirements, the process measurement update (indicated by arrow 42 in FIG. 2) is much faster than the control routine execution rate (indicated by arrow 40 in FIG. 2). Fast, and thus much faster than the process response time, or sampled at a higher rate and provided to the controller.

However, obtaining frequent and periodic samples of measurements from the process can be difficult, for example, when the controller is operating in a process control environment in which it wirelessly receives measurements from one or more field devices. Impractical or even impossible. Specifically, in these cases, if the controller can only receive slow or aperiodic process variable measurements (to conserve battery life of the wireless sensor/transmitter) There is Moreover, in these cases, the time between aperiodic and even periodic process variable measurements may be longer than the control routine execution rate (indicated by arrow 40 in FIG. 2). FIG. 3 depicts an exemplary wireless process control system 10 that may implement slow and/or aperiodic wireless communication of process control data or use of process variable measurements at controller 11 .

The control system 10 of FIG. 3 is essentially similar to the control system 10 of FIG. 1 and like elements are numbered the same. However, the control system 10 of FIG. 3 includes a number of field devices 60-64 and 71 communicatively coupled to the controller 11 and potentially to each other. As illustrated in FIG. 3 , wirelessly connected field device 60 is connected to antenna 65 and cooperates in wireless communication with antenna 74 , which in turn communicates with wireless I/O device 68 . concatenated. Additionally, the field devices 61 - 64 are connected to a wired-to-wireless conversion unit 66 which in turn is connected to an antenna 67 . Field devices 61 - 64 communicate wirelessly through antenna 67 with antenna 73 that is connected to a further wireless I/O device 70 . As also illustrated in FIG. 3, field device 71 includes antenna 72 that communicates with one or both of antennas 73 and 74 to thereby communicate with I/O devices 68 and/or 70 . I/O devices 68 and 70 are then communicatively connected to controller 11 via wired backplane connections (not shown in FIG. 3). In this case, field devices 15 - 22 remain hardwired to controller 11 via I/O devices 26 and 28 .

The process control system 10 of FIG. 3 is generally a wireless communication of data measured, sensed, or calculated by transmitters 60-64 or other control elements such as field devices 71, as described below. Use transmission. In control system 10 of FIG. 3, new process variable measurements or other signal values are transmitted to controller 11 by devices 60-64 and 71 on a slow or non-periodic basis, such as when certain conditions are met. considered to be For example, a new process variable measurement may be sent to controller 11 when the process variable value changes by a predetermined amount relative to the last process variable measurement sent to controller 11 by the device. These signals can also be sent periodically, but typically at a much slower rate for typical process control systems such as wired process control signals. For example, the slow periodic feedback rate can be lower than the controller execution rate (the rate at which the controller generates new control signals for use in creating control signals), and also herein Lower than, equal to, or similar to the process response rate or response time, such as a rate 2-4 times lower than the response rate of the process dynamics being controlled using the described control techniques rate. Here, the process response rate is the reciprocal of the process response time. Of course, other methods of determining when to transmit process variable measurements in a periodic or aperiodic manner may also or alternatively be implemented.

As will be appreciated, the transmitters 60-64 of FIG. 3 each transmit a respective process variable (e.g., flow rate, pressure , temperature, or level signal) can be transmitted to the controller 11 . Other wireless devices, such as field device 71, can wirelessly receive process control signals and/or can be configured to transmit other signals indicative of any other process parameter. Generally speaking, as illustrated in FIG. 3, the controller 11 includes a communication stack 80 executing on a processor that processes incoming signals, and a communication stack 80 for detecting when incoming signals contain measurement updates. It includes a module or routine 82 executing on the processor and one or more control modules 84 executing on the processor to provide control based on the measurement updates. Detection routine 82 may generate a flag or other signal to indicate that data provided via communications stack 80 includes a new process variable measurement or other type of update. The new data and update flags can then be provided to one or more of the control modules 84 (which can be functional blocks), which are then provided to the control modules 84, as described in more detail below. is executed by the controller 11 at a predetermined periodic execution rate. Alternatively or additionally, new data and updated flags may be provided to one or more monitoring modules or applications running on controller 11 or other parts of control system 10 .

The wireless (or other) transmitter of FIG. 3 generally results in slow or periodic, irregular or otherwise frequent communication between field devices 60-64 and 71 and controller 11. including low data transmission. However, as noted above, the communication of measurements from the field devices 15-22 to the controller 11 conventionally occurs at a rate much faster than the controller's execution rate, or at least at a process dynamic rate. It is constructed to run in a cyclical fashion at a much faster rate, ie, the inverse of the process response time (for the process phenomenon being controlled). As a result, the control routines of controller 11 are generally designed for periodic updating of process variable measurements used in controller 11 feedback loops.

Accommodates slow, aperiodic, or otherwise unavailable measurement updates (and other unavailable communication transmissions), such as those introduced by wireless communication between some of the field devices and the controller 11 In order to do so, the control and monitoring routine(s) of controller 11, as described below, are designed to monitor these updates, especially when using slow speeds, including aperiodic or intermittent updates. occurs less frequently than the execution rate of the controller 11, and furthermore, such updates are performed at a rate similar to the process response rate (eg, the inverse of the process response time of the process variable being controlled) (eg, 2 ~4 times lower or similar rate, etc.) can be reconfigured or modified to allow the process control system 10 to function properly. 4-10 illustrate in greater detail exemplary control schemes configured to operate using slow and/or aperiodic control related communications. For example, FIG. 4A schematically illustrates a location-type process controller 100 coupled to process 101 . The control scheme implemented by controller 100 (which may be controller 11 of FIGS. 1 and 3, or a control element of a field device, such as one of the wireless field devices of FIG. 3) is generally , including one or more of the communication stack 80 functionality illustrated and described in connection with FIG. A control signal is generated indicating the position to be moved.

In the exemplary system of FIG. 4A, the controller 100 is, for example, from one of the workstations 13 (FIGS. 1 and 3) or any workstation within or in communication with the process control system 10. and operate to generate one or more control signals 105 that are provided to process 101 from the output of controller 100 . In addition to receiving control signal 105 , process 101 may be subject to measured or unmeasured disturbances, indicated schematically by arrow 104 . Depending on the type of process control application, the setpoint signal may be changed at any time during control of process 101, such as by a user, adjustment routine, or the like. Of course, process control signals 105 may control actuators associated with valves, or any other field device to affect the operational response of process 101 . The response of process 101 to changes in process control signal 105 is measured or sensed by a transmitter, sensor, or other field device 106, such as any one of transmitters 60-64 illustrated in FIG. can correspond to The communication link between transmitter 106 and controller 100, which may include a wireless connection, is illustrated in FIG. 4A using dashed lines.

In a simple embodiment, the controller 100 can implement a single-input, single-output closed-loop control routine, such as a PI control routine, which is one form of a PID control routine. Thus, controller 100 includes several standard PI controller elements including communication stack 80 and a control signal generator including summation block 108 , proportional gain element 110 , further summation block 112 and high/low limiter 114 . Control routine 100 also includes a direct feedback path that includes filter 116 and an integral output switch that includes select block 118 . A filter 116 is coupled to the output of the high/low limiter 114 and a block of switches 118 is coupled to the output of the filter 116 to provide the integral or reset contribution or component of the control signal being generated by the controller 100 to the summation block 112 . .

During operation of controller 100, summation block 108 compares the setpoint signal with the most recently received process variable measurement provided from communication stack 80 within controller 100 to generate an error signal. Proportional gain element 110 operates on the error signal, for example, by multiplying the error signal by a proportional gain value K _p to produce a proportional contribution or component of the control signal. Summation block 112 then combines the output of gain element 110 (i.e., the proportional contribution) with the integral or reset contribution, or component of the control signal produced by the feedback path, to produce an essentially unlimited control signal. combine. Limiter block 114 then places a high or low limit on the output of summation block 112 to generate control signal 105 which is sent to control process 101 .

Importantly, filter 116 and block or switch 118 in the feedback path of controller 100 operate in the following manner to generate the integral or reset contribution of the control signal. Filter 116 , coupled to receive the output of limiter 114 , produces an indication of expected process response to control signal 105 based on the output value of limiter 114 and the duration or time of execution of control algorithm 100 . Filter 116 provides this expected process response signal to switch or block 118 . Switch or block 118 samples and clamps the output of filter 116 at the output of switch or block 118 whenever a new process variable measurement is received, and holds this value until the next process variable output is received at communication stack 80 . to maintain Therefore, the output of switch 118 remains the output of filter 116 sampled at the last measurement update.

The expected process response to changes in the output of summer 108, as produced by filter 116, can be approximated using a first order model, as described in more detail below. More generally, however, the expected process response can be generated using any suitable model of process 101, into a model incorporated into the feedback path of controller 100, or into an integral or It is not limited to filters or models associated with determining reset contributions. For example, a controller that utilizes a model to provide expected process responses may incorporate differential contributions such that control routine 100 implements a PID control scheme. Some examples incorporating exemplary types of differential contributions are described below in connection with FIGS.

図４Ａに示されるように、コントローラ１００内でポジティブフィードバック経路を使用する１つの利点は、コントローラ出力が、高くまたは低く、すなわちリミッタ１１４によって制限されるときに、リセット寄与をワインドアップすることが自動的に防止されることである。 Before discussing the operation of filter 116 of FIG. 4A in more detail, it is useful to note that a conventional PI controller can be implemented using a positive feedback network to determine the integral or reset contribution. be. Mathematically, it can be seen that the transfer function for implementing conventional PI is equivalent to the standard equation for unconstrained control, ie, when the output is unlimited. especially:

One advantage of using a positive feedback path within controller 100, as shown in FIG. to be effectively prevented.

In any event, the control techniques described below allow the controller to reset or use a positive feedback path to determine the integral contribution when it receives aperiodic updates of the process variable. , but still allows for robust controller response in the event of setpoint or feedforward changes that occur between receipt of new process variable measurements. Specifically, in order to provide robust setpoint changes to controller operation, filter 116 may be used for each or all runs of controller 100, whether or not this output of the filter is provided to summation block 112. It is configured to calculate a new indication or value of the expected process response during the interval. As a result, even if only the output of filter 116 generated immediately after controller 100 receives a new process measurement update from communication stack 80 is used as an integral or reset contribution in adder 112, the controller During each execution cycle of the routine, the output of filter 116 is regenerated anew.

Specifically, the new indication of the expected response as produced by filter 116 is the current controller output (i.e., the control signal after limiter 114), the last (i.e., immediately preceding) controller execution cycle It is calculated during each controller execution cycle from the indication of the expected response generated by the filter 116 generated during and the duration of the controller's execution. As a result, filter 116 is described herein as being continuously updated as it is executed to generate new process response estimates during each controller execution cycle. Exemplary equations are described below that can be implemented by the continuously updated filter 116 to generate a new expected process response or filter during each controller run cycle.

Here, the new filter output F _N is the previous filter output F _N−1 (that is, the current filter output value) plus the current controller output value ON ₋₁ and the current filter output value F _N−1 . It will be noted that iteratively determined plus a damping component determined by the difference between _{T_Reset} and a factor that depends on the duration of execution ΔT of the controller. By using a filter that continuously updates in this manner, the control routine 100 can better determine the expected process response when calculating the integral control signal input when new process variable measurements are received. , thereby being more sensitive to setpoint changes or other feedforward disturbances that occur between the receipt of two process variable measurements. More specifically, a setpoint change (without receiving a new process measurement) immediately results in a change in the error signal at the output of summer 108, which changes the proportional contribution component of the control signal. , thus changing the control signal. As a result, filter 116 immediately begins generating new expected responses of the process to the changed control signal, thus updating its output before controller 100 receives new process measurements. Then, when controller 100 receives a new process measurement, a sample of the filter output is clamped by switch 118 to the input of summer 112 for use as the integral or reset contribution of the control signal. 116 repeats, at least to some extent, the expected process response that reacted to or incorporated the response of process 101 to setpoint changes.

In the past, reset contribution filters used in aperiodically updated controller feedback paths, such as in the systems described in US Pat. Nos. 7,587,252 and 7,620,460, were: Only new indications of expected response were calculated when new process variable measurements could be used. As a result, the reset contribution filter compensated for setpoint changes or feedforward disturbances that occurred during reception of process variable measurements, as the setpoint changes or feedforward disturbances were completely independent of any measurement updates. didn't. For example, if a setpoint change or feedforward disturbance occurs between two measurement updates, the calculation of the new indication of expected response is based on the time since the last measurement update and the current controller output 105. Therefore, the expected process response of the controller could be distorted. As a result, filter 116 compensates for time variations in the process (or control signal) resulting from setpoint changes (or other feedforward disturbances) that occur between receipt of two process variable measurements at the controller. couldn't get started.

As will be appreciated, however, the control routine 100 of FIG. 4A provides the expected process response by being based on the calculation of aperiodic measurements, while in addition, changes in setpoint (or controller Determine the expected response between receiving two measurements to compensate for changes caused by any measured disturbances used as feedforward inputs to 100). Thus, the control techniques described above can adapt to setpoint changes, feedforward actions to measured disturbances, etc. that can affect the expected process response, thus providing a more robust control response. do.

As will be appreciated, the control technique illustrated in FIG. 4A provides an indication of the expected response via a filter 116 (e.g., reset contribution filter) that is continuously updated for each execution of the control block or routine 100. Calculate Here, controller 100 configures continuously updated filter 116 to compute a new indication of the expected response for each execution of the control block. However, to determine whether the output of filter 116 should be used as an input to summation block 112, communication stack 80, and in some embodiments update detection module 82 (FIG. 3), uses a new Incoming data from the transmitter 106 is processed to generate a new value flag for the integrated output switch 118 when a process variable measurement is received. This new value flag tells switch 118 to sample and clamp the filter output value for this controller iteration to the input of adder 112 .

Regardless of whether new value flags are communicated, the continuously updated filter 116 continues to calculate an indication of the expected response for each iteration of the control routine. This new indication of the expected response is conveyed to the integral output switch 118 for each execution of the control block. In response to the presence of the new value flag, the integration output switch 118 enables a new indication of the expected response from the continuously updated filter 116 to pass to the summation block 112 and the control block Toggle between maintaining the signal previously delivered to summation block 112 during the last execution. More specifically, when a new value flag is communicated, the integration output switch 118 passes to the summation block 112 the most recently calculated indication of the expected response from the continuously updated filter 116 . make it possible. Conversely, if there is no new value flag, the Integral Output Switch 118 resends to the summation block 112 an indication of the expected response from the last control block iteration. In other words, the integral output switch 118 clamps to a new indication of the expected response each time a new value flag is communicated from the stack 80, but if no new value flag is present, the integration output switch 118 will clamp to any expected response. The newly calculated indication is also prevented from reaching summation block 112 .

This control technique allows the continuously updated filter 116 to continue to model the expected process response regardless of whether new measurements are communicated. If the control output changes as a result of setpoint changes or feedforward actions based on measured disturbances, regardless of the presence of new value flags, the continuously updated filter 116 is expected at each control routine iteration. Correctly reflect the expected process response by calculating a new indication of the response However, new indications of the expected response (ie, reset contribution or integral component) are only incorporated into the controller's calculations when a new value flag is communicated (via integral output switch 118).

Graph 200 illustrated in FIG. 4B illustrates the simulated behavior of controller 100 of FIG. 4A in driving process output signal 202 to a steady state value as controller 100 responds to several setpoint changes. Depict. In FIG. 4B, the process output signal 202 (illustrated as a thick line) is shown compared to the setpoint signal 204 (illustrated as a thin line) during wireless operation of the process control system. As indicated by the arrows along the bottom time axis of graph 200, when a setpoint change occurs, controller 102 resets the new setpoint (i.e., steady state) by generating a control signal that drives the process output. state value). For example, as illustrated in FIG. 4B, _a setpoint change occurs at time T1, which is evident from the large change in magnitude of setpoint signal 204 from a higher value to a lower value. be. In response, the controller 102 drives the setpoint or process variable associated with the setpoint value to the new steady state in _a smooth transient curve such as that exhibited by the output signal ₂₀₂ between time T1 and time T2. . Similarly, in FIG. 4B, the _second setpoint change occurs at time T2, as evidenced by the large change in magnitude of setpoint signal 204 from a lower value to a higher value. . _In response, controller 102 controls the setpoint or process variable associated with the setpoint value to the new steady state in a smooth transient curve as indicated by output signal ₂₀₂ between times T2 and T3. . As a result, as can be seen from FIG. 4B, the controller 100 implementing the control routine described above enables compensation for setpoint changes in an aperiodic wireless control system in a robust manner. Since feedforward disturbances can be measured and included in control action operations, the controller 100 implementing the control routines described above can also compensate for feedforward changes in control output in aperiodic wireless control systems. can be

The simple PI controller configuration of FIG. 4A directly uses the output of filter 116 as the reset contribution to the control signal, in this case the reset contribution of the closed-loop control routine (e.g., the continuously updated Note that the filter equation) can provide an accurate representation of the process response in determining whether the process exhibits steady state operation. However, other processes, such as dead-time dominated processes, may require additional components to be incorporated into the controller of FIG. 4A to model the expected process response. For processes that are well represented by first-order models, in general, process time constants can be used to determine the reset time of a PI (or PID) controller. More specifically, if the reset time is set equal to the process time constant, the reset contribution generally overrides the proportional contribution such that the control routine 100 reflects the expected process response over time. do. In the example illustrated in FIG. 4A, the reset contribution can be achieved by a positive feedback network having a filter with the same time constant as the process time constant. Although other models can be used, positive feedback networks, filters, or models provide a convenient mechanism for determining the expected response of processes with known or approximate process time constants. For processes requiring PID control, the differential contribution, also known as rate, to the PID output can be recalculated and updated only when new measurements are received. In such cases, the derivative calculation can use the elapsed time since the last new measurement. Although other controller components can be used to control more complex processes using aperiodic reception of process measurements, FIG. 4A is used to provide robust control in response to setpoint changes. Some examples of controllers that can use the filtering technique of are described below in conjunction with FIGS.

Referring now to FIG. 5, an alternative controller (or control element) 120, configured according to the control techniques described above, is similar in many respects to the controller 100 illustrated in FIG. 4A. As a result, elements common to both controllers are identified with the same reference numbers. However, controller 120 incorporates additional elements into the control routine, which determines the expected process response during transmission of measurements. In this case, the process 101 can be characterized as having a significant amount of dead time, so that a dead time unit or block 122 is included in the controller model for dead time correction. Incorporating the dead time unit 122 generally helps arrive at a more accurate representation of the process response. More specifically, dead-time unit 122 may be implemented in any desired manner and may include or utilize methods common to Smith predictors or other known control routines. However, in this situation, the continuously updated filter 116 and switch module 118 are the same as described above with respect to the controller 100 of FIG. 4A to provide robust control in response to setpoint changes. Works in style.

FIG. 6 depicts another alternative controller (or control element) 130 that differs from the controller 100 described above in FIG. 4A in that a derivative or rate contribution component is incorporated into controller 130 . By incorporating derivative contributions, the control routines implemented by controller 130 include additional feedback mechanisms such that, in some instances, a proportional-integral-derivative (PID) control scheme is implemented.

The control routine or technique of FIG. 6 includes a derivative contribution configured in a manner similar to that described above in connection with the integral contribution of FIG. adapt to unavailable updates. Differential contributions can be reconstructed based on elapsed time since the last measurement update. In this manner, spikes in the derivative contribution (and resulting output signal) are avoided. More specifically, the derivative contribution of FIG. 6 is determined by a derivative block 132 that receives the error signal from summation block 108 in parallel with the elements dedicated to the proportional and integral contributions. The proportional, integral, and derivative contributions are combined in summation block 134 as shown in FIG. 6, although other PID configurations (eg, serial configurations) may also be utilized.

To accommodate unreliable transmission and, more generally, the unavailability of measurement updates, the differential contribution is delayed until a measurement update is received, as indicated by the new value flag from communication stack 80 . is maintained at the value determined by This technique allows the control routine to continue periodic execution according to the control routine's normal or established execution rate. Upon receiving updated measurements, derivative block 132 may determine the derivative contribution according to the following equation, as illustrated in FIG.

This technique for determining differential contributions allows measurement updates to process variables (ie, control inputs) to be lost over one or more execution periods without generating output spikes. When communication is re-established, the term (e _N −e _N−1 ) in the differential contribution equation can generate the same value as generated in the standard calculation of the differential contribution. However, for standard PID techniques, the divisor in determining the differential contribution is the execution period. In contrast, the present control technique utilizes the elapsed time between two successfully received measurements. By using an elapsed time longer than the execution period, the control technique produces a smaller derivative contribution than the standard PID technique, and spiking is reduced.

To facilitate the determination of elapsed time, communication stack 80 may provide a new value flag, described above, to differentiation block 132, as shown in FIG. Alternate embodiments may include or involve detection of new measurements or updates based on that value. Also, process measurements can be used in place of errors in calculating the proportional or derivative components. More generally, communication stack 80 may include any software, hardware, or software to implement a communication interface with process 101, including any field devices within process 101, process control elements external to the controller, and the like. or firmware (or any combination thereof). However, in controller 130 of FIG. 6, continuously updated filter 116 and switch module 118 are described above with respect to controller 100 of FIG. 4A to provide robust control in response to setpoint changes. works like a thing.

Controller-controlled actuators or other downstream elements described in connection with FIGS. 3, 4A, and 5-6 are particularly After a period of time without any communication in between, it may still receive control signals with abrupt changes. The resulting control action may, in some instances, be abrupt enough to affect plant operation, and such abrupt changes may lead to inappropriate levels of instability. .

The possibility of abrupt control changes due to loss of communication between the controller and downstream elements means that when determining the feedback contribution(s) to the control signal, during the last execution period, the actual can be addressed by incorporating data downstream of Generally speaking, such actual downstream data provides a feedback indication of the response to the control signal and thus the downstream element (e.g. process control module) or device (e.g. actuator ) can be measured or calculated by Such data is provided in lieu of implicit responses to control signals, such as controller outputs from the last run. As shown in FIGS. 4A and 5-6, continuously updated filter 116 receives control signal 105 as an implicit indication of its downstream response. The use of such implicit data effectively assumes that downstream elements, such as actuators, have received communication of control signals, and are therefore responding appropriately to the control signals. Actual feedback data also differs from other response indications, such as measurements of process variables being controlled.

FIG. 7 depicts an exemplary controller 140 that receives actuator position data from downstream devices or elements in response to control signals. A downstream device or element often corresponds to the actuator and provides a measurement of actuator position. More generally, a downstream device or element may correspond to or include a PID control block, control selector, splitter, or any other device or element controlled by a control signal. In the exemplary case shown, the actuator position data is provided as an indication of the response to the control signal. Actuator position data is therefore utilized by the controller 140 during continuous execution of the control routine despite the lack of process variable measurement updates. To this end, the continuously updated filter 116 can receive actuator position data via a communication stack 146 that establishes an interface for incoming feedback data. In this illustrative case, the feedback data includes two indications of response to control signals, actuator position, and process variables.

As with the previous embodiment, the continuously updated filter 116 is configured to adapt to situations involving lack of measurement updates for process variables. Continuously updated filter 116 maintains its output during such absences as well, despite the fact that only the filter output generated after receiving a new measurement flag is used by adder 112. recalculate to However, upon receiving measurement updates, the continuously updated filter 116 no longer relies on control signal feedback to modify its output. Rather, the actual response data from the actuators are utilized as shown below.

The use of actual indications of responses to control signals is useful for control techniques, both during periodic communication and after non-periodic communication or loss of communication from PID control elements to downstream elements, e.g., actuators. It can help improve accuracy. However, transmission of the actual response indication typically requires additional communication between the field device and the controller when implemented in different devices. Such communications may be wireless, as described above, and thus may be subject to unreliable transmission or power limitations. Other reasons may also lead to unavailability of feedback data.

As described below, the control techniques discussed herein can also handle situations where such response indications are not communicated in a periodic or timely manner. That is, the application of this control technique need not be limited to the lack of process variable measurement updates. Rather, the present control technique can be advantageously employed to address situations involving the lack of other responsive indications such as the position of actuators or the output of downstream control elements. Still further, the present control technique may prevent loss of transmission from a controller (or control element) to a downstream element such as a field device (e.g., actuator) or another control element (e.g., cascaded PID control, splitter, etc.); Can be used to address situations involving delays or other unavailability.

Wireless or other unreliable transmission of additional data (i.e., response indications or feedback of downstream elements) to or from the controller or control elements (i.e., control signals) Provides additional possibilities for communication problems and/or challenges. As explained above, feedback from downstream elements (eg, actuators) can be involved in determining the integral contribution (or other control parameter or contribution). In this embodiment, the control routine relies on two feedback signals rather than a single process variable fed back in the embodiment described above. Furthermore, the process does not benefit from the control scheme if the control signal has never reached the downstream element. Transmission of any one of these signals may be delayed or lost, and thus the techniques described herein address both possibilities.

The lack of response indications involved in filters or other control calculations can be addressed by maintaining indications of expected responses (or other control signal components) until an update is received.

When the control signal does not reach the downstream element, the response indication (ie, feedback) from the downstream element does not change. In such cases, the lack of change in value causes the controller (or control element) to similarly maintain indications of the expected response (or other control signal component) until a change in value is received. Logic can be triggered.

The control technique can also be implemented in situations where actual feedback data is not desired or available. The former case may be advantageous in situations where simplicity is beneficial, such as using implicit responses to control signals. For example, communication of actual feedback data may be problematic or impractical. The latter case may involve actuators or other devices that are not configured to provide position measurement data, as described above. Older devices may not have such capabilities.

To accommodate such devices, switches or other devices may be provided to allow the control techniques to use either implicit or actual response indications. As illustrated in FIG. 8, controller 150 is coupled to switch 152 and thus receives both implicit and actual response indications. In this case, the controller 150 can be identical to any of the controllers described above, as implementation of the control scheme does not depend on knowing the type of response indication. Switch 152 may be implemented in software, hardware, firmware, or any combination thereof. Control of switch 152 may be independent of controller 150 and implementation of any control routines. Alternatively or additionally, controller 150 may provide control signals to configure switch 152 . Additionally, switch 152 may be implemented as part of the controller itself, or in some cases may be integrated as part of the communication stack or other part of the controller.

Implementation of the control methods, systems, and techniques is not limited to any one specific radio architecture or communication protocol. Suitable exemplary architectures and communication support schemes are described in U.S. patent application Ser. The entire disclosure of which is incorporated herein by reference. In fact, the modifications to the control routine are well suited to any situation where the control routine is implemented in a periodic fashion, but without process variable measurements for each control iteration. Other exemplary situations include when sampled values are provided irregularly or infrequently, for example by an analyzer or via laboratory samples.

Implementation of the present control technique is not limited to use with single-input, single-output PID control routines (including PI and PD routines), but rather many different multiple-input and/or multiple-output control schemes; as well as cascaded control schemes. More generally, the control technique also applies to any closed-loop model-based control involving one or more process variables, one or more process inputs, or other control signals such as model predictive control (MPC). It can also be applied in routine situations.

FIG. 9 illustrates a further exemplary control system that uses the principles described herein but is configured with a controller 300 in the form of a velocity-based controller. In the exemplary system of FIG. 9, the controller 300 may be, for example, from one of the workstations 13 (FIGS. 1 and 3) or any workstation within or in communication with the process control system. It operates to receive setpoint signals from other sources and generate one or more control signals 305 that are provided to process 301 from the output of controller 300 . In addition to receiving control signals 305, process 301 may be subject to measured or unmeasured disturbances, indicated schematically by arrows 304 in FIG. Depending on the type of process control application, the setpoint signal may be changed at any time during control of process 301, such as by a user, adjustment routine, or the like. Of course, process control signals 305 may control actuators associated with valves, or any other field device to affect the operational response of process 301 . The response of process 301 to changes in process control signal 305 is measured or sensed by a transmitter, sensor, or other field device 306, such as any one of transmitters 60-64 illustrated in FIG. can correspond to The communication link between transmitter 306 and controller 300, which may include a wireless connection, is illustrated in FIG. 9 using dashed lines. However, this link could also be a wired communication link or other type of communication link. For the purposes of discussion, the transmitter 306 is assumed to be measuring a controlled process variable (i.e., controlled variable) or a proxy variable correlated with the controlled process variable at a slow or intermittent update rate. It is regarded. This slow update rate can be periodic or aperiodic and is considered to be of the same order of magnitude as the process response rate of the process dynamics associated with the controlled process variable. Thus, process variable measurements are provided once per time interval longer than the process response time, once per time interval similar to the process response time, or once per time interval slightly shorter than the process response time. Therefore, in some cases, this update rate can be 1/2 to 1/4 the process response rate (the reciprocal of the process response time).

In the simple embodiment illustrated in FIG. 9, the controller 300 can implement a single-input, single-output closed-loop control routine, such as a PI control routine, which is one form of a PID control routine. be. Thus, controller 300 includes several standard PI controller elements including communication stack 380 and a control signal generator including summation block 308 , proportional gain element 310 and further summation block 312 . The control routine 300 also includes a direct integral feedback path including a filter 316 and an integral output switch that includes a select block 318 . However, in this case, the PI controller of FIG. 9 is configured to perform position and differential control calculations for the proportional and integral components of the control signal. Accordingly, the controller 300 also includes a difference block 320 arranged in the proportional component calculation path, an adder 322 arranged in the integral component calculation path, and a differentially calculated control component there to produce the control signal 305. It also includes a block 324 that is used as an input to the . Generally speaking, block 324 scales changes in the position (velocity) control signal when generated within controller 300, or otherwise converts this signal into an analog signal sent to the control device. Or converted to a digital signal, directing the control device to move a certain amount in one direction or another for a certain period of time. This block 324 may, for example, transmit a pulse width modulated signal, a pulse signal, a digital signal indicative of turn-on time, or any other signal indicative of the magnitude of change in position to the control device over time.

As illustrated in FIG. 9, integration filter 316 is coupled to the output of adder 322, which in turn is coupled to receive the output of adder 312, while switch block 318 It is coupled to the output of filter 316 to provide summation block 312 with an integral or reset contribution or component of the control signal being generated by controller 300 .

During each iteration or operation of controller 300, summation block 308 combines the setpoint signal and the most recently received process variable measurement provided from communication stack 380 within controller 300 to produce an error signal (e). Compare with A proportional gain element or block 310 operates on the error signal e, for example, by multiplying the error signal e by a proportional gain value _Kp to produce a proportional contribution or component of the velocity control signal. Difference block 320 then determines the difference since the last controller iteration by determining the difference between the current output of gain block 310 (generated during the last or previous controller iteration) and the previous value of gain block 310 . Determines the change in the proportional gain value of Summing block 312 then combines the output of variation unit 320 (i.e., the proportional contribution based on velocity) with the control signal produced by the integral feedback path to produce velocity control signal 326 which is provided to output block 324. Combine with integral or reset contribution or component.

Importantly, however, summer 322, filter 316, and block or switch 318 in the integral feedback path of controller 300 operate in the following manner to generate the integral or reset contribution of the control signal. where summer 322 is coupled to receive the output of summer 312 (i.e., the velocity-based control signal representing the change in position of the moveable control element) during each controller iteration; That value is summed with the previous output S of adder 322 (generated during the last iteration of controller 300), thereby effectively giving the change in output signal change over a specified period of time. Integrate or sum. The new output S of adder 322 is provided to integration filter 316, which produces an indication of the expected process response to control signal 305, denoted R in FIG. Filter 316 provides this expected process response signal R to switch or block 318 . However, as shown in FIG. 9, switch or block 318 samples and clamps the output of filter 316 at the output of switch or block 318 whenever a new process variable measurement is received, but otherwise , provides a zero (0.0) value to adder 312 as the integral control contribution during control iterations in which no new process variable measurements are available. Thus, the output of switch 318, which is provided as the integral control contribution to generate a new control signal during each controller iteration, is available for new process variable measurements for use by controller 300 during the controller iteration. is the output of filter 316 only when , and is zero (0.0) otherwise. Each time the new value flag generated by communication stack 380 is set (indicating that a new process variable measurement is available in controller 300), adder 322 sets the output to zero, over a new period of time. Start counting. Thus, in effect, adder 322 sums the change in control output signal over each controller iteration between process variable measurement changes and receives new process variable measurement updates at controller 300 (during the controller iteration). always reset after

The expected process response to changes in the control signal, such as produced by filter 316, can be approximated using a first order model, as described in more detail below. More generally, however, the expected process response can be generated using any suitable model of the process 301, into a model incorporated into the feedback path of the controller 300, or into an integral or It is not limited to filters or models associated with determining reset contributions. For example, a controller that utilizes a model to provide expected process responses may incorporate differential contributions such that control routine 300 implements a PID control scheme. One example incorporating exemplary differential contributions is described below in connection with FIG.

In any event, the control techniques described below allow the controller 300 to use a positive feedback path to determine the reset or integral contribution when slow or aperiodic updates of the process variable are received. but still allows robust controller response in the event of setpoint changes or feedforward changes that occur between receipt of new process variable measurements. Specifically, filter 316 may be used to estimate the expected process response during each or every run of controller 300, whether or not this output of filter 316 was provided to summation block 312 as the integral component of the control signal. Configured to calculate new indications or values. As a result, only the output of filter 316 that is generated immediately after controller 300 receives a new process measurement update from communication stack 380 (or during its execution cycle) is used as the integral or reset contribution of adder 312. During each execution cycle of the controller routine, the output of filter 316 is regenerated anew, even if there is.

Specifically, the new indication of expected response R as produced by filter 316 is the current adder output S (i.e., the control output by adder 312 since the last process variable measurement update). signal), an indication of the expected response produced by filter 316 produced during the last (i.e., immediately preceding) controller execution cycle, and the duration of the controller execution cycle. be done. As a result, filter 316 is described herein as being continuously updated as it is executed to generate new process response estimates during each controller execution cycle. Exemplary equations are described below that can be implemented by the continuously updated filter 316 to generate a new expected process response or filter during each controller execution cycle.

Here, the new filter output R _N is the previous filter output R _N−1 (ie, the current filter output value) plus the summed change S _N−1 of the current controller output value from adder 322 and the current Note that it is determined repeatedly, plus a damping component determined by the difference between the filter output value R _N-1 plus a factor dependent on the reset time T _Reset and the duration of execution ΔT of the controller. Will. By using a filter that continuously updates in this manner, the control routine 300 can better determine the expected process response when calculating the integral control signal input when new process variable measurements are received. , thereby being more sensitive to setpoint changes or other feedforward disturbances that occur between the receipt of two process variable measurements. However, this integral path calculation prevents the control system from winding up in the presence of slowly received or intermittent process variable feedback measurements. More specifically, a setpoint change (without receiving a new process measurement) immediately results in a change in the error signal at the output of adder 308, which changes the proportional contribution component of speed control signal 326 to , and thus change the control signal 305 . As a result, adder 322 increases its output S by that amount, and filter 316 then immediately begins generating a new expected response of the process to the changed control signal, thus enabling controller 300 to generate a new process measurement. Update the output before receiving the value. Filter 316 is then clamped to the input of summer 312 by switch 318 so that the controller 100 receives a new process measurement and a sample of the filter output is used as the integral or reset contribution of the control signal. repeats the expected process response, at least in part, based on the previously transmitted control signal 305, in response to or incorporating the response of the process 301 to setpoint changes. However, in order to allow the error signal e produced by adder 308 to reflect changes in the process variable during the time the process variable measurements are received at controller 300, this integral value is a new It is only added to the control signal 326 when the measurements are received. In the controller iterations during which process variable measurements are received, the integral element provided to summer 312 is set to zero. This technique prevents or aids control system 300 from winding up. In effect, the integral element produced by filter 316 estimates the process response during the time that subsequent process variable feedback is received (controller iteration), and the actual process variable response is as expected. , the integral component sets the value produced in the proportional path to zero when a new process variable measurement is received at the controller 300 . If the expected response of the process differs from the actual process response during this time, the integral component changes the control signal 326 to move the actuator, thereby modifying the position of the actuator.

In the past, reset contribution filters used in aperiodically updated controller feedback paths, such as in the systems described in US Pat. Nos. 7,587,252 and 7,620,460, were: Only new indications of expected response were calculated when new process variable measurements could be used. As a result, the reset contribution filter compensated for setpoint changes or feedforward disturbances that occurred during reception of process variable measurements, as the setpoint changes or feedforward disturbances were completely independent of any measurement updates. didn't. For example, if a setpoint change or feedforward disturbance occurs between two measurement updates, the calculation of the new indication of expected response is based on the time since the last measurement update and the current controller output 305. Therefore, the expected process response of the controller could be distorted. As a result, filter 316 compensates for time variations in the process (or control signal) resulting from setpoint changes (or other feedforward disturbances) that occur between receipt of two process variable measurements at the controller. couldn't get started.

As will be appreciated, however, the control routine 300 of FIG. 9 provides an expected process response by basing calculations being made on slow or non-periodic measurements, while adding determines the expected response between receiving two measurements to compensate for changes caused by setpoint changes (or any measured disturbances used as feedforward inputs to controller 300). do. Thus, the control techniques described above can adapt to setpoint changes, feedforward actions to measured disturbances, etc. that can affect the expected process response, thus providing a more robust control response. do. In addition, this control technique avoids windup in the controller, so that when the feedback rate of the process variable measurement is equal to or even lower than the reciprocal of the process response time (i.e., the feedback being received at the controller It can work effectively when the time between measurements is longer than the process response time).

As will be appreciated, the control technique illustrated in FIG. 9 provides an indication of the expected response via a filter 316 (e.g., reset contribution filter) that is continuously updated for each execution of the control block or routine 300. Calculate Here, controller 300 configures continuously updated filter 316 to compute a new indication of the expected response for each execution of the control block. However, if the output of filter 316 is to be used as an input to summation block 312, communications stack 380 and, in some embodiments, update detection module 82 (FIG. 3), may use the new process variable measurement value is received, the incoming data from transmitter 306 is processed to generate new value flags for integral output switch 318 and adder 326 . This new value flag tells switch 318 to sample and clamp the filter output value for this controller iteration to the input of adder 312 . Alternatively, switch 318 provides a zero (0.0) value to adder 312 as the integral contribution value.

Regardless of whether new value flags are communicated, the continuously updated filter 316 continues to calculate an indication of the expected response for each iteration of the control routine. This new indication of the expected response is conveyed to the integral output switch 318 for each execution of the control block. In response to the presence of the new value flag, the integration output switch 318 allows a new indication of the expected response from the continuously updated filter 316 to pass through to the summation block 312; Maintaining a zero value on input to 312. More specifically, when a new value flag is communicated, the integration output switch 318 outputs the previously or currently calculated indication of the expected response from the continuously updated filter 316 to the summation block 312 . allows you to pass to Conversely, if there are no new value flags, integral output switch 318 provides a zero value to adder 312 .

After or when a new process variable measurement is received at the controller 300 and the output R of the continuous filter 316 is used at the adder 312, the time since last communication is set to zero (0) and continuously The filter output R is set to zero. Similarly, the output of adder 322 is set to zero (0). Additionally, in these situations, adder 312 subtracts successive filter outputs R from the output of block 320 to generate new control signals 326, depending on the manner or order in which block 320 performs the difference calculation. can do.

This control technique allows the continuously updated filter 316 to continue to model the expected process response regardless of whether new measurements are communicated. If the control output changes as a result of setpoint changes or feedforward action based on measured disturbances, regardless of the presence of new value flags, the continuously updated filter 316 will be the expected value at each control routine iteration. reflect the expected process response by calculating a new indication of the response However, new indications of the expected response (i.e. reset contribution or integral component) are only incorporated into the calculation of the controller output signal when a new value flag is communicated (via integral output switch 318). prevents or reduces controller windup in response to slow received process variable measurements at the controller 300 .

The simple PI controller configuration of FIG. 9 directly uses the output of filter 316 as the reset contribution to the control signal, in this case the reset contribution of the closed-loop control routine (e.g., the continuously updated Note that the filter equation) can provide an accurate representation of the process response that determines whether the process exhibits steady state operation. However, other processes, such as dead-time dominated processes, may be improved by including a dead-time unit in the integral computation path to model the expected process response, as illustrated in FIGS. Additionally, it may be necessary to incorporate additional components into the controller of FIG. For processes that are well represented by first-order models, in general, process time constants can be used to determine the reset time of a PI (or PID) controller. More specifically, if the reset time is set equal to the process time constant, the reset contribution generally overrides the proportional contribution such that the control routine 300 reflects the expected process response over time. do. In the example illustrated in FIG. 9, the reset contribution can be achieved by a positive feedback network having a filter with the same time constant as the process time constant. Although other models can be used, positive feedback networks, filters, or models provide a convenient mechanism for determining the expected response of processes with known or approximate process time constants. For processes requiring PID control, the differential contribution, also known as rate, to the PID output can be recalculated and updated only when new measurements are received. In such cases, the derivative calculation can use the elapsed time since the last new measurement. 9 to provide robust control in response to setpoint changes, although other controller components can be used to control more complex processes using aperiodic reception of process measurements. An example of a controller that can use the filtering technique of is described below in conjunction with FIG.

Specifically, FIG. 10 depicts an alternative controller (or control element) 400 that differs from controller 300 described above in FIG. 9 in that a derivative or rate contribution component is incorporated into controller 400 . By incorporating derivative contributions, the control routines implemented by controller 400 include additional feedback mechanisms such that, in some instances, a proportional-integral-derivative (PID) control scheme is implemented.

The control routine or technique of FIG. 10 includes a differential contribution configured in a manner similar to that described above in connection with the system of FIGS. subject to updates that are not available or are otherwise unavailable. Differential contributions can be reconstructed based on elapsed time since the last measurement update. In this manner, spikes in the derivative contribution (and resulting output signal) are avoided. More specifically, the derivative contribution in the system of FIG. 10 is determined by the derivative block 432, which is derived from the gain block 310 (multiplied by the proportional gain _Kp ) in parallel with the elements dedicated to the proportional and integral contributions. It receives the error signal and operates to produce a derivative control component _OD , which is then provided to change block 433 . Change block 433 determines the change in the derivative control component _OD since the last controller iteration and provides this change to adder 434 which puts the change in the derivative control component on the output of adder 312. Summing or adding to generate a change in control signal. In this case, adder 322 of the integral contribution computation path is connected to the output of adder 434 . However, the components of FIG. 10 that are also illustrated in FIG. 9 operate in the manner described with respect to FIG. Here, the derivative block 432 operates to calculate a new derivative component _OD only during controller iterations in which it receives a new value flag (indicating that a new value for the process variable measurement has been received at the controller). you will know to do. This action effectively keeps the output of change block 434 at zero for all controller iterations while or at the time no new process variable measurement is received at controller 400 .

To accommodate unreliable transmission and, more generally, the unavailability of measurement updates, the differential contribution _OD is kept until it receives a measurement update, as indicated by the new value flag from communication stack 380 . , is maintained at the last determined value. This technique allows the control routine to continue periodic execution according to the control routine's normal or established execution rate. Upon receiving updated measurements, the derivative block 432 can determine the derivative contribution according to the following equation, as illustrated in FIG.

Of course, if desired, the derivative component calculation block 432 can be connected directly to the output of summer 308 to receive the error signal, and the derivative gain term _KD is the derivative gain with proportional gain _KP can be set to include This technique for determining differential contributions causes measurement updates to process variables (i.e., control inputs) to be lost or unavailable over one or more run sequences without generating output spikes. , which allows for bumpless recovery. When communication is re-established, or when a new process variable measurement is received at the controller, the term (e _N −e _N−1 ) of the differential contribution equation is generated in the standard calculation of the differential contribution. You can generate the same value as the value. However, for standard PID techniques, the divisor in determining the differential contribution is the execution period. In contrast, the present control technique utilizes the elapsed time between two successfully received measurements. By using an elapsed time longer than the execution period, the control technique produces a smaller derivative contribution than the standard PID technique, and spiking is reduced.

To facilitate the determination of elapsed time, communication stack 80 may provide the new value flags described above to differentiation block 432, as shown in FIG. Alternate embodiments may include or involve detection of new measurements or updates based on that value. Also, process measurements can be used in place of errors in calculating the proportional or derivative components. More generally, communications stack 380 may include any software, hardware, or software to implement a communications interface with process 301, including any field devices within process 301, process control elements external to the controller, and the like. or firmware (or any combination thereof). However, in controller 400 of FIG. 10, continuously updated filter 316 and switch module 318 are described above with respect to controller 300 of FIG. 9 to provide robust control in response to setpoint changes. works like a thing.

Implementation of the control methods, systems, and techniques described herein are not limited to any one specific wireless architecture or communication protocol. Suitable exemplary architectures and communication support schemes are described in U.S. patent application Ser. The entire disclosure of which is incorporated herein by reference. In fact, the modifications to the control routine are well suited to any situation in which the control routine is implemented in a periodic fashion, but without process variable measurements for each control iteration. Other exemplary situations include when sampled values are provided irregularly or infrequently, for example by an analyzer or via laboratory samples.

Implementation of the present control technique is not limited to use with single-input, single-output PID control routines (including PI and PD routines), but rather many different multiple-input and/or multiple-output control schemes; as well as cascaded control schemes. More generally, the control technique also applies to any closed-loop model-based control involving one or more process variables, one or more process inputs, or other control signals such as model predictive control (MPC). It can also be applied in routine situations.

11-14 provide graphical depictions of the simulated operation of the control routines described herein (specifically, the operation of FIG. 10) in which the process response time is A standard velocity form PID control algorithm was used to illustrate the effectiveness of the present control routine in situations similar to or even shorter than the time between updated process variable measurements. A comparison is made with a prior art controller. The graphs of FIGS. 11-14 illustrate examples of simulated control using only primary control, although other types of control, such as override control, can be used. Generally speaking, each of the graphs of FIGS. 11A, 12A, 13A, and 14A illustrate the operation of a standard prior art speed-based PID control algorithm, which is based on the new Both a wired feedback configuration (whose operation is illustrated on the left side of the graph) and a wireless configuration (whose operation is illustrated on the right side of the graph) in which process variable measurements are available during each controller iteration. to use. However, FIGS. 11A and 13A illustrate a control situation with a feedback rate or time between process variable measurements of 8 seconds and a process response time of 8 seconds, while FIGS. It illustrates the operation of a prior art controller with a feedback rate or time between variable measurements of 8 seconds and a process response time of 3 seconds. Similarly, FIGS. 11 and 12 illustrate controller operation in response to setpoint changes, while FIGS. 13 and 14 illustrate these same controller operations in response to disturbance changes. For comparison, the graphs of FIGS. 11B, 12B, 13B, and 14B show the speeds described herein under the same process control conditions as FIGS. 11A, 12A, 13A, and 14A, respectively. illustrates the operation of the PID algorithm based on

Generally speaking, the following parameters were used in the simulated control operations depicted in FIGS. against set point changes and unmeasured disturbances. The control and process simulations used in the tests were set up as follows.
Test for 8 sec process response First order process (same gains and kinetics)
process gain = 1
Process time constant = 8 seconds Process dead time = 0 seconds Adjustment of PID to first order (lambda factor 1.0)
Proportional gain = 1
Integral gain = 7.5 repetitions/min Test for process response 1st order process (same gain and kinetics)
process gain = 1
Process time constant = 3 seconds Process dead time = 0 seconds Adjustment of PID to first order (lambda factor 1.0)
Proportional gain = 1
Integral Gain = 20 repetitions/minute Module Execution Rate 0.5 seconds Radio Update Rate for all tests 8 seconds Periodic Disturbance Input for all tests Affects primary measurements only Gain = 1

As illustrated in FIGS. 11A and 13A, the prior art speed-based PID control algorithm uses a wired configuration and a wired configuration where the process response time is equal to the interval between process variable measurements (both set at 8 seconds). Both in the radio configuration, it works more or less satisfactorily in response to setpoint changes (FIG. 11A) and to disturbance changes (FIG. 13A). However, as indicated by the circled portions of the graphs in FIGS. 11A and 13A, this control technique causes large variations in valve position during response during wireless control. As illustrated in FIGS. 11B and 13B, the control techniques described herein perform somewhat better in these situations (setpoint change in FIG. 11B and disturbance change in FIG. 13B), Very similar in action.

However, as illustrated in FIGS. 12A and 14A, the prior art velocity-based PID controller provides a setpoint change and disturbance change at a process response time of 3 seconds and a process variable update rate of 8 seconds. does not work very well and actually becomes unstable during radio control in response to both. However, as illustrated in FIGS. 12B and 14B, the current speed-based control routine still performs very satisfactorily in these situations, with the process variable measurement update interval time being less than the process response time. Large (long) and even significantly larger (eg, 2-4 times) illustrate the effectiveness of the presently described control routine.

The term "field device" is used herein to refer to any device or combination of devices (i.e., a device that provides multiple functions, such as a transmitter/actuator hybrid), as well as any device that performs a function in a control system. is used broadly to include other device(s) of In any event, field devices include, for example, input devices (e.g., devices such as sensors and instruments that provide status, measurements, or other signals indicative of process control parameters such as temperature, pressure, flow, etc.), and controllers. and/or control operators or actuators that take action in response to commands received from other field devices such as valves, switches, flow control devices, and the like.

Note that any control routine or module described herein may have portions thereof implemented or executed distributed across multiple devices. As a result, a control routine or module can have portions that are implemented by different controllers, field devices (eg, smart field devices) or other devices, or other control elements, as desired. Similarly, the control routines or modules implemented within the process control system described herein may take any form, including software, firmware, hardware, and the like. Any device or element involved in providing such functionality may have software, firmware, or associated hardware located in a controller, field device, or any other device within a process control system. may be generally referred to herein as a "control element," regardless of whether it is located on a device (or collection of devices). A control module may be any part or portion of a process control system including, for example, routines, blocks, or any element thereof stored on any computer-readable medium. Such control modules, control routines, or any portion (e.g., block) thereof, may be implemented or executed by any element or device of a process control system, generally referred to herein as a control element. can be done. A control routine, which can be a module or any part of a control procedure such as a subroutine, part of a subroutine (such as a sequence of code), can be implemented using object-oriented programming, or ladder logic, sequential functions, etc. It can be implemented in any desired software format using charts, functional block diagrams, or using any other software programming language or design paradigm. Similarly, control routines may be hard-coded into, for example, one or more EPROMs, EEPROMs, application specific integrated circuits (ASICs), or any other hardware or firmware elements. Still further, the control routines can be designed using any design tool, including graphical design tools, or any other type of software/hardware/firmware programming or design tools. Accordingly, controller 11 may be configured to implement control strategies or routines in any desired manner.

Alternatively or additionally, the functional blocks can be stored on and implemented by the field devices themselves or other control elements of the process control system, if the system utilizes fieldbus devices. obtain. Although control system descriptions are provided herein using a function block control strategy, control techniques and systems may also use other conventions such as ladder logic, sequential function charts, or any It can also be implemented or designed using any other desired programming language or paradigm.

When implemented, any of the software described herein may be stored on any computer readable medium, such as a magnetic disk, laser disk , or other storage medium, computer or processor RAM or ROM. can be stored in memory. Similarly, the software may be stored on, for example, a computer readable disk or other portable computer storage mechanism, or communication channels such as telephone lines, the Internet, the World Wide Web, any other local area network, or wide area network. Any known or desired distribution method may be used to distribute to users, process plants, or operator workstations using any known or desired method of distribution, including delivery of such software via portable storage media. considered to be the same as or compatible with). Further, this software may be provided directly without modulation or encryption, or may be modulated and encrypted using any suitable modulating carrier and/or encryption technique before being transmitted over a communication channel. /or can be encrypted.

Thus, although the present invention has been described with reference to specific embodiments that are intended to be illustrative only and not limiting, it will be appreciated by those skilled in the art that the spirit of the present invention It will be apparent that modifications, additions, or omissions may be made to the control techniques without departing from the scope and scope.

Claims (6)

A method of controlling a process comprising:
implementing a plurality of iterations of a control routine on a computer processing device to generate a control signal, during each iteration of said control routine comprising:
using a computer processing device to generate an integral feedback contribution for use in generating the control signal, during each of the plurality of iterations, including the current iteration of the control routine; for the current iteration of the control routine from the integral feedback contribution value of the previous iteration of the control routine and the summed value of the control signal for all previous iterations since the last iteration in which a new process variable measurement was received ; generating, including using a continuously updated iterative filter to determine a current integral feedback contribution value;
to generate the control signal for the current iteration of the control routine based on a determination by a switch connected to the continuously updated iteration filter during each controller iteration that receives a new process variable measurement ; any integral feedback for generating the control signal based on the determination by the switch during controller iterations using the current integral feedback contribution and not receiving new process variable measurements for the control signal; performing, including using no contribution or using a zero value;
and using the control signal to control the process. 2. The method of claim 1, further comprising generating a proportional contribution during each iteration and using the proportional contribution during each iteration to generate the control signal. 3. The method of claim 1 or 2, wherein the process variable measurements are measurements of process parameters affected by the control signal. 4. The method of claim 3, wherein the process parameter is a process variable controlled by a field device responsive to the control signal. Determining the integral feedback contribution may include a difference between the control signal for the current iteration of the control routine and the integral feedback contribution value for the previous iteration of the control routine, a reset time and a controller execution period. A method according to any one of claims 1 to 4, comprising generating the integral feedback contribution value based on multiplied by a factor dependent on . performing multiple iterations of the control routine to generate the control signal;
(i) during each iteration of the control routine, generating the control signal based on a setpoint value, a previous process variable measurement, and the integral feedback contribution; and (ii) each of the control routines. generating a proportional component during an iteration from a setpoint value, the most recently received process variable measurement , and a proportional gain value; and generating the proportional component during the current iteration and the previous iteration. generating the control signal using the difference between the proportional component of
The method according to any one of claims 1 to 5, comprising at least one of

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