CN106814613A - A kind of two input and output network decoupling and controlling system random delay mixed control methods - Google Patents

Abstract

Two input and output network decoupling and controlling system (TITO NDCS) random delay mixed control methods, belong to the MIMO NDCS technical fields of limited bandwidth resources.Affect one another and couple between a kind of two input/output signal, need the TITO NDCS by decoupling treatment, transmit produced network delay among the nodes due to network data, not only influence the stability of respective close loop control circuit, but also the stability of whole system will be influenceed, even result in the problem that TITO NDCS lose stabilization, propose with the network data transmission process between all real nodes in TITO NDCS, instead of the method for network delay compensation model therebetween, SPC and IMC are implemented respectively to two loops simultaneously, the measurement to network delay between node can be exempted, estimate or recognize, reduce clock signal synchronization requirement, reduce influence of the random delay to TITO NDCS stability, improve quality of system control.

Description

A kind of two input and output network decoupling and controlling system random delay mixed control methods

Technical field

The present invention relates to automatic control technology, the crossing domain of the network communications technology and computer technology, more particularly to band The multiple-input and multiple-output network decoupling and controlling system technical field of resource-constrained wide.

Background technology

In dcs, between sensor and controller, controller and actuator, by Real Time Communication Network The closed-loop feedback control system of composition, referred to as network control system (Networked control systems, NCS), NCS's Typical structure is as shown in Figure 1.

NCS compared with the control system of traditional point-to-point structure, with low cost, be easy to information sharing, be easy to extension With safeguard, flexibility is big the advantages of, process automation, automated manufacturing, Aero-Space, nothing be widely used in recent years The multiple fields such as line communication, robot, intelligent transportation.

In NCS, due to the presence of the phenomenons such as network delay, data packetloss and network congestion so that NCS faces many New challenge.The especially presence of random network time delay, it is possible to decrease the control quality of NCS, or even make system loss of stability, sternly System may be caused to break down during weight.

At present, the research on NCS both at home and abroad, primarily directed to single-input single-output (Single-input and Single-output, SISO) network control system, respectively known to network delay, it is unknown or random, network delay be less than one The individual sampling period transmits more than a sampling period, the transmission of list bag or many bags, when whetheing there is data-bag lost, it is entered Row mathematical modeling or stability analysis and controlling.But in actual industrial process, generally existing including at least two inputs With two control systems of output (Two-input and two-output, TITO), the multiple-input and multiple-output for being constituted The research of (Multiple-input and multiple-output, MIMO) network control system is then relatively fewer, especially Needed by decoupling the multiple-input and multiple-output network uneoupled control for processing between input and output signal, there is coupling The achievement in research of system (Networked decoupling control systems, NDCS) delay compensation is then relatively less.

The typical structure of MIMO-NDCS is as shown in Figure 2.

Compared with SISO-NCS, MIMO-NDCS has the characteristics that：

(1) affected one another between input and output signal and there is coupling

In the MIMO-NCS that there is coupling, a change for input signal will become multiple output signals Change, and each output signal is also not only influenceed by an input signal.Even if by meticulous between input and output signal Selection pairing, also exists and influences each other unavoidably between each control loop, thus to make output signal independently tracked respective defeated Enter signal to have any problem.Decoupler in MIMO-NDCS, for releasing or reducing the coupling between MIMO signal Effect.

(2) internal structure is more more complex than SISO-NCS

(3) controlled device there may be uncertain factor

In MIMO-NDCS, the parameter being related to is more, and the contact between each control loop is more, and parameter variations are to overall control The influence of effect processed can become very complicated.

(4) control unit failure

In MIMO-NDCS, including at least there is two or more close loop control circuits, including at least have two or More than two sensors and actuator.The failure of each element may influence the performance of whole control system, when serious Control system can be made unstable, or even caused a serious accident.

Due to the above-mentioned particularity of MIMO-NDCS so that be mostly based on SISO-NCS be designed with control method, The requirement of the control performance of MIMO-NDCS and control quality cannot have been met, prevent its from or be not directly applicable MIMO- In the design and analysis of NDCS, control and design to MIMO-NDCS bring certain difficulty.

For MIMO-NDCS, network delay compensation is essentially consisted in the difficult point of control：

(1) due to network delay and network topology structure, communication protocol, offered load, the network bandwidth and data package size It is relevant etc. factor, to more than several or even the dozens of sampling period random network time delay, to set up each control in MIMO-NDCS The Mathematical Modeling that the random network time delay in loop processed is accurately predicted, estimates or recognized, is nearly impossible at present.

(2) occur when previous node in MIMO-NDCS is to network during latter node-node transmission network data Prolong, no matter using which kind of prediction or method of estimation in previous node, be impossible to know the net for producing thereafter in advance in advance Network time delay exact value.Time delay cause systematic function decline in addition cause system unstable, while also to control system analysis with Design brings difficulty.

(3) to meet in MIMO-NDCS, all node clock signal Complete Synchronizations in different distributions place are unrealistic 's.

(4) due in MIMO-NCS, being affected one another between input and output, and there is coupling, its MIMO-NDCS's Internal structure is more complicated than MIMO-NCS and SISO-NCS, it is understood that there may be uncertain factor it is more, it is implemented time delay benefit Repay more much more difficult than MIMO-NCS and SISO-NCS with control.

The content of the invention

The present invention relates to a kind of two input two in MIMO-NDCS export network decoupling and controlling system (TITO-NDCS) with The compensation of machine time delay and control, the typical structure of its TITO-NDCS are as shown in Figure 3.

For the close loop control circuit 1 in Fig. 3：

1) from input signal x₁S () arrives output signal y₁S the closed loop transfer function, between () is：

In formula：C₁S () is control unit, G₁₁S () is controlled device；τ₁Representing will control decoupler CD output signal nodes u_1pS (), the random network time delay that actuator A1 nodes are experienced is transferred to through preceding to network path；τ₂Represent output signal y₁ (s) from sensor S1 nodes, through the random network time delay that feedback network tunnel is experienced to control decoupler CD nodes.

2) from C in close loop control circuit 2₂The output signal u of (s) control unit₂S (), is transmitted by cross decoupling passage Function P₁₂S () acts on close loop control circuit 1, from input signal u₂S () arrives output signal y₁Closed loop transfer function, between (s) For：

3) from the output signal u of actuator A2 nodes in close loop control circuit 2_2p(s), by controlled device cross aisle Transmission function G₁₂S () influences the output signal y of close loop control circuit 1₁(s), from input signal u_2pS () arrives output signal y₁(s) Between closed loop transfer function, be：

The denominator of above-mentioned closed loop transfer function, equation (1) to (3)In, when containing random network Prolong τ₁And τ₂Exponential termWithThe presence of time delay loses the performance quality of control system, the system of even resulting in is deteriorated Stability.

For the close loop control circuit 2 in Fig. 3：

1) from input signal x₂S () arrives output signal y₂S the closed loop transfer function, between () is：

In formula：C₂S () is control unit, G₂₂S () is controlled device；τ₃Representing will control decoupler CD output signal nodes u_2pS (), the random network time delay that actuator A2 nodes are experienced is transferred to through preceding to network path；τ₄Represent output signal y₂ (s) from sensor S2 nodes, through the random network time delay that feedback network tunnel is experienced to control decoupler CD nodes.

2) from C in close loop control circuit 1₁The output signal u of (s) control unit₁S (), is transmitted by cross decoupling passage Function P₂₁S () acts on close loop control circuit 2, from input signal u₁S () arrives output signal y₂Closed loop transfer function, between (s) For：

3) from the output signal u of the actuator A1 nodes of close loop control circuit 1_1pS (), is passed by controlled device cross aisle Delivery function G₂₁S () influences the output signal y of close loop control circuit 2₂(s), from input signal u_1pS () arrives output signal y₂(s) it Between closed loop transfer function, be：

The denominator of above-mentioned closed loop transfer function, equation (4) to (6)In, contain random network Delay, τ₃And τ₄Exponential termWithThe presence of time delay will deteriorate the performance quality of control system, even result in system mistake Go stability.

Goal of the invention：

For the TITO-NDCS of Fig. 3, in the denominator of the closed loop transfer function, equation (1) to (3) of its close loop control circuit 1, Contain random network delay, τ₁And τ₂Exponential termWithAnd the closed loop transfer function, of close loop control circuit 2 etc. In the denominator of formula (4) to (6), random network delay, τ is contained₃And τ₄Exponential termWithThe presence of time delay can drop The control performance quality of low respective close loop control circuit simultaneously influences the stability of respective close loop control circuit, while will also decrease whole The control performance quality of individual system simultaneously influences the stability of whole system, and whole system loss of stability will be caused when serious.

Therefore, for the close loop control circuit 1 in Fig. 3：The present invention proposes a kind of based on SPC (Smith Predictor Control, SPC) delay compensation method；For close loop control circuit 2：The present invention proposes a kind of based on IMC (Internal Model Control, IMC) delay compensation method：Constitute the compensation of two close loop control circuit network delays and mix control, In exempting to each close loop control circuit, the measurement of random network time delay, estimation or identification between node, and then reduce network Delay, τ₁And τ₂, and τ₃And τ₄To respective close loop control circuit and steady with system to whole control system control performance quality Qualitatively influence；When prediction model is equal to its true model, it is capable of achieving not wrapped in the characteristic equation of respective close loop control circuit Exponential term containing network delay, and then influence of the network delay to whole system stability can be reduced, improve the dynamic of system Energy quality, realizes the segmentation to TITO-NDCS random network time delays, real-time, online and dynamic predictive compensation and mixes control.

Using method：

For the close loop control circuit 1 in Fig. 3：

The first step：In order to realize meeting during predictive compensation condition, no longer wrapped in the closed loop transform function of close loop control circuit 1 Exponential term containing network delay, to realize to network delay τ₁And τ₂Compensation with control, use to control decoupling signal u_1p(s) And u_2pS () is used as input signal, controlled device prediction model G_11m(s) and G_12mS () is used as controlled process, control and process data By network transfer delay prediction modelAndAround controller C₁S (), constructs a positive feedback Prediction Control loop With a negative-feedback Prediction Control loop, as shown in Figure 4；

Second step：In for actual TITO-NDCS, it is difficult to obtain the problem of network delay exact value, to realize in fig. 4 Compensation and control to network delay, in addition to the condition that controlled device prediction model to be met is equal to its true model, must also Random network Time-delay Prediction model must be metAndTo be equal to its true modelAndCondition.Therefore, From sensor S1 nodes to control decoupler CD nodes, and from control decoupler CD nodes to actuator A1 nodes it Between, using real network data transmission processAndInstead of the predict-compensate model of network delay therebetweenAndThus no matter whether the prediction model of controlled device is equal to its true model, can realize not including from system architecture The predict-compensate model of network delay therebetween, so that in exempting to close loop control circuit 1, random network delay, τ between node₁With τ₂Measurement, estimate or recognize；When prediction model is equal to its true model, it is capable of achieving to its random network delay, τ₁And τ₂'s Compensation and SPC；The network delay compensation for implementing the inventive method is as shown in Figure 5 with SPC structures；

For the close loop control circuit 2 in Fig. 3：

The first step：In decoupler CD nodes are controlled, an internal mode controller C is built first_2IMCS () is used to replace control Device C₂(s)；In order to realize meeting during predictive compensation condition, network is no longer included in the closed loop transform function of close loop control circuit 2 The exponential term of time delay, to realize to network delay τ₃And τ₄Compensation with control, use to control decoupling signal u_1p(s) and u_2p (s) and u_p21S () is used as input signal, controlled device prediction model G_22m(s) and G_21mS () is used as controlled process, control and mistake Number of passes evidence transmits prediction model by network delayAndAround internal mode controller C_2IMCS (), constructs a positive feedback Prediction Control loop and a negative-feedback Prediction Control loop, as shown in Figure 4；

Second step：In for actual TITO-NDCS, it is difficult to obtain the problem of network delay exact value, to realize in fig. 4 Compensation and control to network delay, in addition to the condition that controlled device prediction model to be met is equal to its true model, must also Random network Time-delay Prediction model must be metAndTo be equal to its true modelAndCondition.Therefore, From sensor S2 nodes to control decoupler CD nodes, and from control decoupler CD nodes to actuator A2 nodes it Between, using real network data transmission processAndInstead of the predict-compensate model of network delay therebetweenWith AndThus no matter whether the prediction model of controlled device is equal to its true model, can realize not wrapping from system architecture Predict-compensate model containing network delay therebetween, so that in exempting to close loop control circuit 2, random network delay, τ between node₃ And τ₄Measurement, estimate or recognize；When prediction model is equal to its true model, it is capable of achieving to its random network delay, τ₃And τ₄ Compensation and IMC；The network delay compensation for implementing the inventive method is as shown in Figure 5 with IMC structures.

For the close loop control circuit 1 in Fig. 5：

1) from input signal x₁S () arrives output signal y₁S the closed loop transfer function, between () is：

In formula：G_11mS () is controlled device G₁₁The prediction model of (s).

2) from internal mode controller C in close loop control circuit 2_2IMCThe output IMC signals u of (s)₂(s), by cross decoupling Channel transfer function P₁₂S () acts on close loop control circuit 1, from input IMC signals u₂S () arrives output signal y₁Between (s) Closed loop transfer function, is：

3) from the output signal u that decoupler CD nodes are controlled in close loop control circuit 2_2p(s), in control decoupler CD By controlled device cross aisle transmission function prediction model G_12mS () acts on close loop control circuit 1；Returned from closed-loop control The control signal u of the actuator A2 nodes of road 2_2p(s), while passing through controlled device cross aisle transmission function G₁₂S () is estimated with it Model G_12mS () acts on close loop control circuit 1；From input signal u_2pS () arrives output signal y₁Closed loop transmission letter between (s) Number is：

Using the inventive method, when controlled device prediction model is equal to its real model, that is, work as G_11m(s)=G₁₁(s) When, the closed loop transform function of close loop control circuit 1 will be byBecome 1+ C₁(s)G₁₁(s)=0, no longer comprising the network delay τ of the influence stability of a system in its closed loop transform function₁And τ₂Exponential termWithSo as to influence of the network delay to the stability of a system can be reduced, improve the dynamic control performance quality of system, realize To the dynamic compensation of random network time delay and SPC.

For the close loop control circuit 2 in Fig. 5：

1) from input signal x₂S () arrives output signal y₂S the closed loop transfer function, between () is：

In formula：G_22mS () is controlled device G₂₂The prediction model of (s)；C_2IMCS () is internal mode controller.

2) from controller C in close loop control circuit 1₁The output signal u of (s)₁S (), letter is transmitted by cross decoupling passage Number P₂₁S () acts on close loop control circuit 2, from input signal u₁S () arrives output signal y₂Closed loop transfer function, between (s) For：

3) from cross decoupling channel transfer function P₂₁The output signal u of (s) unit_p21S (), acts on control decoupler The prediction model G of controlled device in CD node controls loop 2_22m(s), from input signal u_p21S () arrives output signal y₂(s) it Between closed loop transfer function, be：

4) from the output signal u that decoupler CD nodes are controlled in close loop control circuit 1_1p(s), in control decoupler CD By controlled device cross aisle transmission function prediction model G_21mS () acts on close loop control circuit 2；Returned from closed-loop control The control signal u of the actuator A1 nodes of road 1_1p(s), while passing through controlled device cross aisle transmission function G₂₁S () is estimated with it Model G_21mS () acts on close loop control circuit 2；From input signal u_1pS () arrives output signal y₂Closed loop transmission letter between (s) Number is：

Using the inventive method, when controlled device prediction model is equal to its real model, that is, work as G_22m(s)=G₂₂(s) When, the closed loop transfer function, denominator of close loop control circuit 2 will be byBecome 1.

Now, close loop control circuit 2 is equivalent to an open-loop control system, in the denominator of closed loop transfer function, no longer Network delay τ comprising the influence stability of a system₃And τ₄Exponential termWithThe stability of system only with controlled device and Controller stability in itself is relevant；So as to influence of the network delay to the stability of a system can be reduced, improve the dynamic control of system Performance quality processed, realizes to the dynamic compensation of random network time delay and IMC.

In close loop control circuit 1, controller C₁The selection of (s)：

Controller C₁S () can be according to controlled device G₁₁The Mathematical Modeling of (s), and model parameter change, both may be selected Conventional control strategy, also may be selected Based Intelligent Control or complex control strategy；Close loop control circuit 1 uses SPC methods, from TITO- Realized in NDCS structures and specific controller C₁S the selection of the control strategy of () is unrelated.

In close loop control circuit 2, internal mode controller C_2IMCThe design of (s) and selection：

Design internal mode controller typically uses pole-zero cancellation method, i.e. two step design methods：The first step is that design one takes it It is the inversion model of plant model as feedforward controller C₂₂(s)；Second step is that certain order is added in feedforward controller Feedforward filter f₂S (), constitutes a complete internal mode controller C_2IMC(s)。

(1) feedforward controller C₂₂(s)

Error, the interference of system when first ignoring controlled device and plant model Incomplete matching and other are various about The factors such as beam condition, in selection close loop control circuit 2, controlled device prediction model is equal to its true model, i.e.,：G_22m(s)=G₂₂ (s)。

Now, controlled device prediction model can be divided into according to the poles and zeros assignment situation of controlled device：G_22m(s)= G_22m+(s)G_22m-(s), wherein：G_22m+S () is controlled device prediction model G_22mPure lag system and s RHPs are included in (s) The irreversible part of zero pole point；G_22m-S () is the reversible part of minimum phase in controlled device prediction model.

Under normal circumstances, the feedforward controller C of close loop control circuit 2₂₂S () can be chosen for：

(2) feedforward filter f₂(s)

The thing of feedforward controller can be influenceed due to the pure lag system in controlled device and positioned at the zero pole point of s RHPs Reason is realisation, thus the reversible part G of controlled device minimum phase has only been taken in the design process of feedforward controller_22m-(s), Ignore G_22m+(s)；There is error due to possible Incomplete matching between controlled device and controlled device prediction model, in system Interference signal is there is likely to be, these factors are likely to make system lose stabilization.Therefore, being added in feedforward controller certain The feedforward filter of order, for reducing influence of the factors above to the stability of a system, improves the robustness of system.

Generally the feedforward filter f of close loop control circuit 2₂S (), is chosen for fairly simple n₂Rank wave filterWherein：λ₂It is feedforward filter time constant；n₂It is the order of feedforward filter, n₂=n_2a-n_2b；n_2aFor Controlled device G₂₂The order of (s) denominator；n_2bIt is controlled device G₂₂The order of (s) molecule, usual n₂＞ 0.

(3) internal mode controller C_2IMC(s)

The internal mode controller C of close loop control circuit 2_2IMCS () can be chosen for:

Be can be seen that from equation (14)：The internal mode controller C of one degree of freedom_2IMCIn (s), the adjustable ginseng of only one of which Number λ₂；Due to λ₂The change of parameter suffers from direct relation with the tracking performance of system and antijamming capability, therefore in filter of adjusting The customized parameter λ of ripple device₂When, the tracing property generally required in system is traded off between the two with antijamming capability.

The scope of application of the invention：

A kind of two input two for being equal to its true model suitable for controlled device prediction model exports network uneoupled control system Unite (TITO-NDCS) random network time delay compensation and mix SPC and IMC；Its Research Thinking and method, are equally applicable to be controlled Object prediction model is equal to the two or more input of its true model and exports constituted multiple-input and multiple-output network decoupling control The compensation of system (MIMO-NDCS) random network time delay processed and mix SPC and IMC.

It is a feature of the present invention that the method is comprised the following steps：

For close loop control circuit 1：

(1) is h when the sensor S1 nodes cycle₁Sampled signal trigger when, employing mode A is operated；

(2) is when control decoupler CD nodes are by feedback signal y_1bWhen () triggers s, employing mode B is operated；

(3) is when actuator A1 nodes are by control decoupling signal u_1pWhen () triggers s, employing mode C is operated；

For close loop control circuit 2：

(4) is h when the sensor S2 nodes cycle₂Sampled signal trigger when, employing mode D is operated；

(5) is when control decoupler CD nodes are by feedback signal y_2bWhen () triggers s, employing mode E is operated；

(6) is when actuator A2 nodes are by control decoupling signal u_2pWhen () triggers s, employing mode F is operated；

The step of mode A, includes：

A1:Sensor S1 nodes work in time type of drive, and its trigger signal is cycle h₁Sampled signal；

A2:After sensor S1 nodes are triggered, to controlled device G₁₁The output signal y of (s)₁₁S () and controlled device are intersected Channel transfer function G₁₂The output signal y of (s)₁₂(s), and actuator A1 nodes output signal y_11mb(s) and y_12mbS () enters Row sampling, and calculate the system output signal y of close loop control circuit 1₁(s) and feedback signal y_1b(s), and y₁(s)=y₁₁(s) +y₁₂(s) and y_1b(s)=y₁(s)-y_11mb(s)-y_12mb(s)；

A3:Sensor S1 nodes are by feedback signal y_1b(s), by the feedback network path of close loop control circuit 1 to control Decoupler CD node-node transmissions, feedback signal y_1bS () will experience network transfer delay τ₂Afterwards, control decoupler CD sections are got to Point；

The step of mode B, includes：

B1:Control decoupler CD nodes work in event driven manner, by feedback signal y_1bS () is triggered；

B2:In decoupler CD nodes are controlled, by the system Setting signal x of close loop control circuit 1₁S (), subtracts feedback letter Number y_1b(s) and controlled device cross aisle transmission function prediction model G_12mThe output valve y of (s)_12maS () and controlled device are pre- Estimate model G_11mThe output valve y of (s)_11maS (), obtains system deviation signal e₁(s), i.e. e₁(s)=x₁(s)-y_1b(s)-y_12ma (s)-y_11ma(s)；

B3:To e₁S () implements control algolithm C₁S (), obtains control signal u₁(s)；

B4:Internal Model Control Algorithm C in close loop control circuit 2 will be come from_2IMCThe output IMC signals u of (s)₂S () acts on Decoupling cross aisle transmission function P₁₂S () obtains its decoupling signal u_p12(s)；By control signal u₁(s) and u_p12S () is subtracted each other and is obtained The control decoupling signal u of close loop control circuit 1_1p(s), i.e. u_1p(s)=u₁(s)-u_p12(s)；By u_1pS () acts on controlled device Prediction model G_11mS () obtains its output valve y_11ma(s)；

B5:The control decoupling signal u that close loop control circuit 2 is exported will be come from_2pS () acts on controlled device cross aisle Transmission function prediction model G_12mS () obtains its output valve y_12ma(s)；

B6:Will control decoupling signal u_1pS feedforward network path that () passes through close loop control circuit 1Unit is to actuator A1 node-node transmissions, u_1pS () will experience network transfer delay τ₁Afterwards, actuator A1 nodes are got to；

The step of mode C, includes：

C1:Actuator A1 nodes work in event driven manner, by control decoupling signal u_1pS () is triggered；

C2:Will control decoupling signal u_1pS () acts on controlled device prediction model G_11mS () obtains its output valve y_11mb (s)；The feedforward network path of close loop control circuit 2 will be come fromThe control decoupling signal u of unit_2pS () acts on controlled right As cross aisle transmission function prediction model G_12mS () obtains its output valve y_12mb(s)；

C3:Will control decoupling signal u_1pS () acts on controlled device G₁₁S () obtains its output valve y₁₁(s)；Control is solved Coupling signal u_1pS () acts on controlled device cross aisle transmission function G₂₁S () obtains its output valve y₂₁(s)；So as to realize to quilt Control object G₁₁(s) and G₂₁The decoupling of (s) and SPC, while realizing to random network delay, τ₁And τ₂Compensation with control；

The step of mode D, includes：

D1:Sensor S2 nodes work in time type of drive, and its trigger signal is cycle h₂Sampled signal；

D2:After sensor S2 nodes are triggered, to controlled device G₂₂The output signal y of (s)₂₂S () and controlled device are intersected Channel transfer function G₂₁The output signal y of (s)₂₁(s), and actuator A2 nodes output signal y_22mb(s) and y_21mbS () enters Row sampling, and calculate the system output signal y of close loop control circuit 2₂(s) and feedback signal y_2b(s), and y₂(s)=y₂₂(s) +y₂₁(s) and y_2b(s)=y₂(s)-y_22mb(s)-y_21mb(s)；

D3:Sensor S2 nodes are by feedback signal y_2b(s), by the feedback network path of close loop control circuit 2 to control Decoupler CD node-node transmissions, feedback signal y_2bS () will experience network transfer delay τ₄Afterwards, control decoupler CD sections are got to Point；

The step of mode E, includes：

E1:Control decoupler CD nodes work in event driven manner, by feedback signal y_2bS () is triggered；

E2:In decoupler CD nodes are controlled, by the system Setting signal x of close loop control circuit 2₂S (), subtracts feedback letter Number y_2b(s) and controlled device cross aisle transmission function prediction model G_21mThe output valve y of (s)_21maS () adds controlled device Prediction model G_22mThe output valve y of (s)_22maS (), obtains system deviation signal e₂(s), i.e. e₂(s)=x₂(s)-y_2b(s)-y_21ma (s)+y_22ma(s)；

E3:To e₂S () implements Internal Model Control Algorithm C_2IMCS (), obtains IMC signals u₂(s)；

E4:Control algolithm C in close loop control circuit 1 will be come from₁The output control signal u of (s)₁S () acts on decoupling and hands over Fork channel transfer function P₂₁S () obtains its decoupling signal u_p21(s)；By IMC signals u₂(s) and u_p21S () subtracts each other and obtains closed loop control The control decoupling signal u in loop processed 2_2p(s), i.e. u_2p(s)=u₂(s)-u_p21(s)；

E5:By decoupling signal u_p21S () acts on controlled device prediction model G_22mS () obtains its output valve y_22ma(s)；Will Come from the control decoupling signal u of the output of close loop control circuit 1_1pS () acts on controlled device cross aisle transmission function and estimates Model G_21mS () obtains its output valve y_21ma(s)；

E6:Will control decoupling signal u_2pS feedforward network path that () passes through close loop control circuit 2Unit is to actuator A2 node-node transmissions, u_2pS () will experience network transfer delay τ₃Afterwards, actuator A2 nodes are got to；

The step of mode F, includes：

F1:Actuator A2 nodes work in event driven manner, by control decoupling signal u_2pS () is triggered；

F2:Will control decoupling signal u_2pS () acts on controlled device prediction model G_22mS () obtains its output valve y_22mb (s)；The feedforward network path of close loop control circuit 1 will be come fromThe control decoupling signal u of unit_1pS () acts on controlled Object cross aisle transmission function prediction model G_21mS () obtains its output valve y_21mb(s)；

F3:Will control decoupling signal u_2pS () acts on controlled device G₂₂S () obtains its output valve y₂₂(s)；Control is solved Coupling signal u_2pS () acts on controlled device cross aisle transmission function G₁₂S () obtains its output valve y₁₂(s)；So as to realize to quilt Control object G₂₂(s) and G₁₂The decoupling of (s) and IMC, while realizing to random network delay, τ₃And τ₄Compensation with control.

The present invention has following features：

1st, due to from exempting in structure in TITO-NDCS, the measurement of random network time delay, observation, estimate or recognize, together When can also exempt the synchronous requirement of node clock signal, time delay can be avoided to estimate the inaccurate evaluated error for causing of model, it is to avoid To expending the waste of node storage resources needed for time-delay identification, while can also avoid due to " sky sampling " or " many that time delay is caused The compensation error that sampling " brings.

2nd, it is unrelated with the selection of specific network communication protocol due to from TITO-NDCS structures, realizing, thus be both applicable In the TITO-NDCS using wired network protocol, the TITO-NDCS of wireless network protocol is also applicable for use with；It is not only suitable for really Qualitative procotol, also suitable for the procotol of uncertainty；The TITO-NDCS of heterogeneous network composition is not only suitable for, while Also it is applied to the TITO-NDCS that heterogeneous network is constituted.

3rd, in TITO-NDCS, using the control loop 1 of SPC, due to being realized from TITO-NDCS structures and specifically controlled Device C₁S the selection of () control strategy is unrelated, thus can be not only used for, using the TITO-NDCS of conventional control, also can be used to use intelligence Can control or the TITO-NDCS using complex control strategy.

4th, in TITO-NDCS, using the control loop 2 of IMC, its internal mode controller C_2IMCS the adjustable parameter of () only has one Individual λ₂Parameter, the regulation of its parameter is simple with selection, and explicit physical meaning；The stabilization of system can be not only improved using IMC Property, tracking performance and interference free performance, but also the compensation to random network time delay and IMC can be realized.

5th, because the present invention uses compensation and control method that " software " changes TITO-NDCS structures, thus at it Any hardware device need not be further added by implementation process, the software resource carried using existing TITO-NDCS intelligent nodes, it is sufficient to Its compensation and control function are realized, hardware investment can be saved and be easy to be extended and applied.

Brief description of the drawings

Fig. 1：The typical structure of NCS

In Fig. 1, system is by sensor S nodes, controller C nodes, actuator A nodes, controlled device, feedforward network path Transmission unitAnd feedback network tunnel unitConstituted.

In Fig. 1：X (s) represents system input signal；Y (s) represents system output signal；C (s) represents controller；U (s) tables Show control signal；τ_caThe feedforward network that control signal u (s) is experienced in expression from controller C nodes to actuator A node-node transmissions Tunnel time delay；τ_scThe feedback net that detection signal y (s) of sensor S nodes is experienced in expression to controller C node-node transmissions Network tunnel time delay；G (s) represents controlled device transmission function.

Fig. 2：The typical structure of MIMO-NDCS

In Fig. 2, system controls decoupler CD nodes by r sensor S node, m actuator A node, controlled device G, M feedforward network tunnel time delayUnit, and r feedback network tunnel time delayUnit is constituted；

In Fig. 2：y_jS () represents j-th output signal of system；u_iS () represents i-th control signal of system；Represent Will control decoupling signal u_iS feedforward network that () is experienced from from control decoupler CD nodes to i-th actuator A node-node transmission leads to Road propagation delay time；Represent j-th detection signal y of sensor S nodes of system_jS () passes to control decoupler CD nodes Defeated experienced feedback network tunnel time delay；G represents controlled device transmission function.

Fig. 3：The typical structure of TITO-NDCS

In Fig. 3, system is made up of close loop control circuit 1 and 2, and system includes sensor S1 and S2 node, control decoupling Device CD nodes, actuator A1 and A2 node, controlled device transmission function G₁₁(s) and G₂₂(s) and controlled device cross aisle Transmission function G₂₁(s) and G₁₂(s), cross decoupling channel transfer function P₂₁(s) and P₁₂(s), feedforward network tunnel unitWithAnd feedback network tunnel unitWithConstituted.

In Fig. 3：x₁(s) and x₂S () represents system input signal；y₁(s) and y₂S () represents system output signal；C₁(s) and C₂S () represents the controller of control loop 1 and 2；u₁(s) and u₂S () represents control signal；u_1p(s) and u_2pS () represents control solution Coupling signal；τ₁And τ₃Represent u_1p(s) and u_2pS () experiences from control decoupler CD nodes to actuator A1 and A2 node-node transmission Feedforward network tunnel time delay；τ₂And τ₄Represent the detection signal y of sensor S1 and S2 node₁(s) and y₂S () is to control The feedback network tunnel time delay of decoupler CD node-node transmissions experience.

Fig. 4：A kind of TITO-NDCS random delay compensation comprising prediction model and control structure

In Fig. 4,AndIt is network transfer delayAndPrediction model；AndIt is network Propagation delay timeAndPrediction model；G_11m(s) and G_22mS () is controlled device transmission function G₁₁(s) and G₂₂(s) Prediction model；G_12m(s) and G_21mS () is controlled device cross aisle transmission function G₁₂(s) and G₂₁The prediction model of (s)；C_2IMC S () is the internal mode controller of control loop 2.

Fig. 5：A kind of two input and output network decoupling and controlling system random delay mixed control methods

Fig. 5 can be realized to the compensation of random network time delay in close loop control circuit 1 and 2 and SPC and IMC.

Specific embodiment

Exemplary embodiment of the invention will be described in detail by referring to accompanying drawing 5 below, make the ordinary skill of this area Personnel become apparent from features described above of the invention and advantage.

Specific implementation step is as described below：

For close loop control circuit 1：

The first step：Sensor S1 nodes work in time type of drive, and its trigger signal is cycle h₁Sampled signal；When After sensor S1 nodes are triggered, to controlled device G₁₁The output signal y of (s)₁₁S () and controlled device cross aisle transmit letter Number G₁₂The output signal y of (s)₁₂(s), and actuator A1 nodes output signal y_11mb(s) and y_12mbS () is sampled, and Calculate the system output signal y of close loop control circuit 1₁(s) and feedback signal y_1b(s), and y₁(s)=y₁₁(s)+y₁₂(s) and y_1b(s)=y₁(s)-y_11mb(s)-y_12mb(s)；

Second step：Sensor S1 nodes are by feedback signal y_1b(s), by the feedback network path of close loop control circuit 1 to Control decoupler CD node-node transmissions, feedback signal y_1bS () will experience network transfer delay τ₂Afterwards, control decoupler CD is got to Node；

3rd step：Control decoupler CD nodes work in event driven manner, by feedback signal y_1bS () triggers after, will System Setting signal x₁S (), subtracts feedback signal y_1b(s) and controlled device cross aisle transmission function prediction model G_12m(s) Output valve y_12ma(s) and controlled device prediction model G_11mThe output valve y of (s)_11maS (), obtains system deviation signal e₁(s), That is e₁(s)=x₁(s)-y_1b(s)-y_12ma(s)-y_11ma(s)；

4th step：To e₁S () implements control algolithm C₁S (), obtains control signal u₁(s)；Close loop control circuit will be come from Internal Model Control Algorithm C in 2_2IMCThe output IMC signals u of (s)₂S () acts on decoupling cross aisle transmission function P₁₂S () obtains it Decoupling signal u_p12(s)；By control signal u₁(s) and u_p12S () subtracts each other the control decoupling signal u for obtaining close loop control circuit 1_1p (s), i.e. u_1p(s)=u₁(s)-u_p12(s)；By decoupling signal u_1pS () acts on controlled device prediction model G_11mS () obtains its defeated Go out value y_11ma(s)；

5th step：The control decoupling signal u that close loop control circuit 2 is exported will be come from_2pS () acts on controlled device intersection Channel transfer function prediction model G_12mS () obtains its output valve y_12ma(s)；

6th step：Will control decoupling signal u_1pS feedforward network path that () passes through close loop control circuit 1Unit is to holding Row device A1 node-node transmissions, u_1pS () will experience network transfer delay τ₁Afterwards, actuator A1 nodes are got to；

7th step：Actuator A1 nodes work in event driven manner, by control decoupling signal u_1pAfter (s) triggering, will control Decoupling signal u processed_1pS () acts on controlled device prediction model G_11mS () obtains its output valve y_11mb(s)；Closed loop will be come from The feedforward network path of control loop 2The control decoupling signal u of unit_2pS () acts on the transmission of controlled device cross aisle Function prediction model G_12mS () obtains its output valve y_12mb(s)；

8th step：Will control decoupling signal u_1pS () acts on controlled device G₁₁S () obtains its output valve y₁₁(s)；Will control Decoupling signal u processed_1pS () acts on controlled device cross aisle transmission function G₂₁S () obtains its output valve y₂₁(s)；So as to realize To controlled device G₁₁(s) and G₂₁The decoupling of (s) and SPC, while realizing to random network delay, τ₁And τ₂Compensation with control；

9th step：Return to the first step；

For close loop control circuit 2：

The first step：Sensor S2 nodes work in time type of drive, and its trigger signal is cycle h₂Sampled signal；When After sensor S2 nodes are triggered, to controlled device G₂₂The output signal y of (s)₂₂S () and controlled device cross aisle transmit letter Number G₂₁The output signal y of (s)₂₁(s), and actuator A2 nodes output signal y_22mb(s) and y_21mbS () is sampled, and Calculate the system output signal y of close loop control circuit 2₂(s) and feedback signal y_2b(s), and y₂(s)=y₂₂(s)+y₂₁(s) and y_2b(s)=y₂(s)-y_22mb(s)-y_21mb(s)；

Second step：Sensor S2 nodes are by feedback signal y_2b(s), by the feedback network path of close loop control circuit 2 to Control decoupler CD node-node transmissions, feedback signal y_2bS () will experience network transfer delay τ₄Afterwards, control decoupler CD is got to Node；

3rd step：Control decoupler CD nodes work in event driven manner, by feedback signal y_2bAfter (s) triggering, will be System Setting signal x₂S (), subtracts feedback signal y_2b(s) and controlled device cross aisle transmission function prediction model G_21m(s) it is defeated Go out value y_21maS () adds controlled device prediction model G_22mThe output valve y of (s)_22maS (), obtains system deviation signal e₂(s), That is e₂(s)=x₂(s)-y_2b(s)-y_21ma(s)+y_22ma(s)；

4th step：To e₂S () implements Internal Model Control Algorithm C_2IMCS (), obtains IMC signals u₂(s)；Closed loop control will be come from Control algolithm C in loop processed 1₁The output control signal u of (s)₁S () acts on decoupling cross aisle transmission function P₂₁S () obtains Its decoupling signal u_p21(s)；By IMC signals u₂(s) and u_p21S () subtracts each other the control decoupling signal u for obtaining close loop control circuit 2_2p (s), i.e. u_2p(s)=u₂(s)-u_p21(s)；

5th step：By decoupling signal u_p21S () acts on controlled device prediction model G_22mS () obtains its output valve y_22ma (s)；The control decoupling signal u that close loop control circuit 1 is exported will be come from_1pS () acts on controlled device cross aisle transmission letter Number prediction model G_21mS () obtains its output valve y_21ma(s)；

6th step：Will control decoupling signal u_2pS feedforward network path that () passes through close loop control circuit 2Unit is to holding Row device A2 node-node transmissions, u_2pS () will experience network transfer delay τ₃Afterwards, actuator A2 nodes are got to；

7th step：Actuator A2 nodes work in event driven manner, by control decoupling signal u_2pAfter (s) triggering, will control Decoupling signal u processed_2pS () acts on controlled device prediction model G_22mS () obtains its output valve y_22mb(s)；Closed loop control will be come from The feedforward network path in loop processed 1The control decoupling signal u of unit_1pS () acts on controlled device cross aisle transmission letter Number prediction model G_21mS () obtains its output valve y_21mb(s)；

8th step：Will control decoupling signal u_2pS () acts on controlled device G₂₂S () obtains its output valve y₂₂(s)；Will control Decoupling signal u processed_2pS () acts on controlled device cross aisle transmission function G₁₂S () obtains its output valve y₁₂(s)；So as to realize To controlled device G₂₂(s) and G₁₂The decoupling of (s) and IMC, while realizing to random network delay, τ₃And τ₄Compensation with control；

9th step：Return to the first step；

The foregoing is only presently preferred embodiments of the present invention and oneself, be not intended to limit the invention, it is all in essence of the invention Within god and principle, any modification, equivalent substitution and improvements made etc. should be included within the scope of the present invention.

The content not being described in detail in this specification belongs to prior art known to professional and technical personnel in the field.

Claims (5)

1. a kind of two input and output network decoupling and controlling system random delay mixed control method, it is characterised in that the method includes Following steps：

For close loop control circuit 1：

(1) is h when the sensor S1 nodes cycle₁Sampled signal trigger when, employing mode A is operated；

(2) is when control decoupler CD nodes are by feedback signal y_1bWhen () triggers s, employing mode B is operated；

(3) is when actuator A1 nodes are by control decoupling signal u_1pWhen () triggers s, employing mode C is operated；

For close loop control circuit 2：

(4) is h when the sensor S2 nodes cycle₂Sampled signal trigger when, employing mode D is operated；

(5) is when control decoupler CD nodes are by feedback signal y_2bWhen () triggers s, employing mode E is operated；

(6) is when actuator A2 nodes are by control decoupling signal u_2pWhen () triggers s, employing mode F is operated；

The step of mode A, includes：

A1:Sensor S1 nodes work in time type of drive, and its trigger signal is cycle h₁Sampled signal；

A2:After sensor S1 nodes are triggered, to controlled device G₁₁The output signal y of (s)₁₁(s) and controlled device cross aisle Transmission function G₁₂The output signal y of (s)₁₂(s), and actuator A1 nodes output signal y_11mb(s) and y_12mbS () is adopted Sample, and calculate the system output signal y of close loop control circuit 1₁(s) and feedback signal y_1b(s), and y₁(s)=y₁₁(s)+y₁₂ (s) and y_1b(s)=y₁(s)-y_11mb(s)-y_12mb(s)；

A3:Sensor S1 nodes are by feedback signal y_1bS (), is decoupled by the feedback network path of close loop control circuit 1 to control Device CD node-node transmissions, feedback signal y_1bS () will experience network transfer delay τ₂Afterwards, get to control decoupler CD nodes；

The step of mode B, includes：

B1:Control decoupler CD nodes work in event driven manner, by feedback signal y_1bS () is triggered；

B2:In decoupler CD nodes are controlled, by the system Setting signal x of close loop control circuit 1₁S (), subtracts feedback signal y_1b (s) and controlled device cross aisle transmission function prediction model G_12mThe output valve y of (s)_12maS () and controlled device estimate mould Type G_11mThe output valve y of (s)_11maS (), obtains system deviation signal e₁(s), i.e. e₁(s)=x₁(s)-y_1b(s)-y_12ma(s)-y_11ma (s)；

B3:To e₁S () implements control algolithm C₁S (), obtains control signal u₁(s)；

B4:Internal Model Control Algorithm C in close loop control circuit 2 will be come from_2IMCThe output IMC signals u of (s)₂S () acts on decoupling Cross aisle transmission function P₁₂S () obtains its decoupling signal u_p12(s)；By control signal u₁(s) and u_p12S () subtracts each other and obtains closed loop The control decoupling signal u of control loop 1_1p(s), i.e. u_1p(s)=u₁(s)-u_p12(s)；By u_1pS () acts on controlled device and estimates Model G_11mS () obtains its output valve y_11ma(s)；

B5:The control decoupling signal u that close loop control circuit 2 is exported will be come from_2pS () acts on the transmission of controlled device cross aisle Function prediction model G_12mS () obtains its output valve y_12ma(s)；

B6:Will control decoupling signal u_1pS feedforward network path that () passes through close loop control circuit 1Unit is saved to actuator A1 Point transmission, u_1pS () will experience network transfer delay τ₁Afterwards, actuator A1 nodes are got to；

The step of mode C, includes：

C1:Actuator A1 nodes work in event driven manner, by control decoupling signal u_1pS () is triggered；

C2:Will control decoupling signal u_1pS () acts on controlled device prediction model G_11mS () obtains its output valve y_11mb(s)；Will Come from the feedforward network path of close loop control circuit 2The control decoupling signal u of unit_2pS () acts on controlled device intersection Channel transfer function prediction model G_12mS () obtains its output valve y_12mb(s)；

C3:Will control decoupling signal u_1pS () acts on controlled device G₁₁S () obtains its output valve y₁₁(s)；By control decoupling letter Number u_1pS () acts on controlled device cross aisle transmission function G₂₁S () obtains its output valve y₂₁(s)；So as to realize to controlled right As G₁₁(s) and G₂₁The decoupling of (s) and SPC, while realizing to random network delay, τ₁And τ₂Compensation with control；

The step of mode D, includes：

D1:Sensor S2 nodes work in time type of drive, and its trigger signal is cycle h₂Sampled signal；

D2:After sensor S2 nodes are triggered, to controlled device G₂₂The output signal y of (s)₂₂(s) and controlled device cross aisle Transmission function G₂₁The output signal y of (s)₂₁(s), and actuator A2 nodes output signal y_22mb(s) and y_21mbS () is adopted Sample, and calculate the system output signal y of close loop control circuit 2₂(s) and feedback signal y_2b(s), and y₂(s)=y₂₂(s)+y₂₁ (s) and y_2b(s)=y₂(s)-y_22mb(s)-y_21mb(s)；

D3:Sensor S2 nodes are by feedback signal y_2bS (), is decoupled by the feedback network path of close loop control circuit 2 to control Device CD node-node transmissions, feedback signal y_2bS () will experience network transfer delay τ₄Afterwards, get to control decoupler CD nodes；

The step of mode E, includes：

E1:Control decoupler CD nodes work in event driven manner, by feedback signal y_2bS () is triggered；

E2:In decoupler CD nodes are controlled, by the system Setting signal x of close loop control circuit 2₂S (), subtracts feedback signal y_2b (s) and controlled device cross aisle transmission function prediction model G_21mThe output valve y of (s)_21maS () is estimated along with controlled device Model G_22mThe output valve y of (s)_22maS (), obtains system deviation signal e₂(s), i.e. e₂(s)=x₂(s)-y_2b(s)-y_21ma(s)+ y_22ma(s)；

E3:To e₂S () implements Internal Model Control Algorithm C_2IMCS (), obtains IMC signals u₂(s)；

E4:Control algolithm C in close loop control circuit 1 will be come from₁The output control signal u of (s)₁S () acts on decoupling intersection logical Road transmission function P₂₁S () obtains its decoupling signal u_p21(s)；By IMC signals u₂(s) and u_p21(s) subtract each other obtain closed-loop control return The control decoupling signal u on road 2_2p(s), i.e. u_2p(s)=u₂(s)-u_p21(s)；

E5:By decoupling signal u_p21S () acts on controlled device prediction model G_22mS () obtains its output valve y_22ma(s)；To come from In the control decoupling signal u of the output of close loop control circuit 1_1pS () acts on controlled device cross aisle transmission function prediction model G_21mS () obtains its output valve y_21ma(s)；

E6:Will control decoupling signal u_2pS feedforward network path that () passes through close loop control circuit 2Unit is saved to actuator A2 Point transmission, u_2pS () will experience network transfer delay τ₃Afterwards, actuator A2 nodes are got to；

The step of mode F, includes：

F1:Actuator A2 nodes work in event driven manner, by control decoupling signal u_2pS () is triggered；

F2:Will control decoupling signal u_2pS () acts on controlled device prediction model G_22mS () obtains its output valve y_22mb(s)；Will Come from the feedforward network path of close loop control circuit 1The control decoupling signal u of unit_1pS () acts on controlled device intersection Channel transfer function prediction model G_21mS () obtains its output valve y_21mb(s)；

F3:Will control decoupling signal u_2pS () acts on controlled device G₂₂S () obtains its output valve y₂₂(s)；By control decoupling letter Number u_2pS () acts on controlled device cross aisle transmission function G₁₂S () obtains its output valve y₁₂(s)；So as to realize to controlled right As G₂₂(s) and G₁₂The decoupling of (s) and IMC, while realizing to random network delay, τ₃And τ₄Compensation with control.

2. method according to claim 1, it is characterised in that：From TITO-NDCS structures, realize system not comprising control The predict-compensate model of all-network time delay in loop 1 and control loop 2, so as to exempt to network delay τ between node₁And τ₂, And τ₃And τ₄Measurement, estimate or recognize, exempt the requirement synchronous to node clock signal.

3. method according to claim 1, it is characterised in that：Realized from TITO-NDCS structures, to random network time delay The implementation of compensation method, the selection with specific network communication protocol is unrelated.

4. method according to claim 1, it is characterised in that：SPC is used for control loop 1, from TITO-NDCS structures Upper realization and specific controller C₁S the selection of () control strategy is unrelated, thus can be not only used for using the TITO- of conventional control NDCS, also can be used for using Based Intelligent Control or the TITO-NDCS using complex control strategy.

5. method according to claim 1, it is characterised in that：IMC is used for control loop 2, system can be improved steady Qualitative and interference free performance, realizes the compensation and control to random network time delay.