CN106940533B - Cloud super real-time simulation platform and hardware-in-loop based real-time decision method - Google Patents
Cloud super real-time simulation platform and hardware-in-loop based real-time decision method Download PDFInfo
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Abstract
The invention discloses a cloud super real-time simulation platform and hardware in-loop based real-time decision method, which relates to the field of industrial automation control system software methods and comprises the steps of reading an input value, writing the input value into a first controller and a second controller, respectively executing logic operation by the first controller and the second controller to obtain a first output variable value and a second output variable value, comparing the second output variable value with a fault tree, if a fault is judged to exist, forcibly writing a third output variable value into the first controller and entering the next step, and if the fault is judged not to exist, directly entering the next step; and judging whether the first output variable value is the same as the second output variable value or whether the third output variable value is the same as the second output variable value, returning to the initial step if the first output variable value is the same as the second output variable value, and assigning the second output variable value to be the first output variable value or the third output variable value according to different conditions and returning to the initial step if the second output variable value is different from the first output variable value.
Description
Technical Field
The invention relates to a software method of an industrial automation control system, in particular to a cloud super real-time simulation platform and hardware-in-the-loop based real-time decision method.
Background
In an industrial automation control system, system simulation mostly follows a Model-View-Controller (MVC) mode, a Model pointer describes physical characteristics and functional behavior characteristics of a control object, and the state of the control object is saved in the simulation process; the view refers to a user visual interface, displays the model state in the simulation process, and allows a user to input parameters and transmit the parameters to the controller; the controller provides a control algorithm that updates algorithm parameters in response to user manipulation. When a change in the control algorithm occurs, the changed state will be sent to the model. And when the model receives the request, the updated behavior characteristics are obtained by calculating the state change through the physical model and are returned to the controller.
The system simulation method mainly comprises two modes of closed-loop simulation and in-loop simulation. In the closed-loop simulation mode, the model and the controller are both in software simulation, and real-time or super-real-time simulation is realized by deploying the model and the controller in a computer, a server or a cloud. In the ring simulation, data exchange with a model running on a computer is realized by deploying a controller to corresponding physical equipment and by means of Ethernet, USB or industrial field bus.
In the long-time operation process of the existing industrial automatic control system, sudden failures without warning often occur in system hardware, and even if the system passes long-time closed-loop simulation verification, unknown software errors and unknown errors under extreme conditions cannot be completely avoided. In addition, the existing loop simulation scheme adopts a full-software simulation method, so that the time period for establishing the model is long, the cost is high, the accuracy is low, and the difference between the simulation result and the real result is large; and the simulation platform mostly carries out super real-time simulation in an off-line mode, and no matter a hardware-in-loop simulation method or a full-software simulation method, real-time intervention on an on-line system according to an off-line simulation result cannot be realized so as to avoid faults.
Disclosure of Invention
In view of the above defects in the prior art, the technical problem to be solved by the present invention is to perform self-diagnosis when a sudden fault occurs during the operation of the industrial automation control system, so as to increase the speed of system fault diagnosis, realize the capability of predicting the fault before the fault occurs, perform real-time intervention on the industrial automation control system, and perform self-repair to avoid the fault.
In order to solve the problems, the invention provides a cloud super real-time simulation platform and hardware-in-the-loop based real-time decision method, which comprises the following steps:
Further, the input values in the step 100 are all input values read through an industrial fieldbus, and the first controller and the second controller read the input values at the same time.
Further, the first controller is an industrial controller, the second controller is a virtual controller, and the second controller is a virtual controller mirror image established by the cloud super real-time simulation platform for the first controller.
Further, the first controller and the second controller simultaneously establish a closed-loop connection with an input device, and the first controller and the second controller periodically read the input value.
Further, the operation logic in step 300 is an actual working logic of the first controller, and the second controller simulates one or more next update cycles by using the operation logic according to the input value.
Further, the failure in step 410 includes a problem causing a system shutdown and a process stop.
Further, the writing of the third output variable value to the first controller in the step 500 is performed in real time, and the cloud super real-time simulation platform sends a force rewrite instruction to the first controller, so as to prevent a fault from occurring.
Further, the decision method is based on a system comprising a cloud super real-time simulation platform, a sensor and an actuator, an industrial controller and industrial system equipment, wherein the cloud super real-time simulation platform and the industrial controller are connected through an industrial Ethernet, the industrial controller and the sensor and the actuator are connected through an industrial field bus, and the sensor and the actuator are connected to the industrial system equipment; the system includes at least one of the sensors, at least one actuator, and at least one of the industrial controllers.
Further, the cloud super real-time simulation platform comprises a communication module, a virtual controller operation stack and a decision auxiliary manager, wherein the communication module reads an input value through an industrial field bus, a sensor and an actuator and writes the input value into the virtual controller operation stack; the virtual controller operation stack comprises one or more virtual controller operation environments, each virtual controller operation environment operates independently, and after the input value is processed, the virtual controller pushes the generated second output variable value to the decision auxiliary manager; and the decision auxiliary manager compares the received second output variable value with fault tree data preset in a cloud super real-time simulation platform database, judges whether a fault occurs according to a comparison result, searches a solution of the corresponding fault from the database and writes the solution back to the industrial controller.
Further, when the system starts to deploy an industrial automation control program, control codes are uploaded to the industrial controller and the virtual controller at the same time.
The invention provides an online real-time decision-making method based on a cloud super real-time simulation platform and equipment mixed ring, which particularly realizes super real-time simulation by using industrial automation control system software, judges equipment faults in advance according to a simulation result, realizes self-protection by a real-time online monitoring means and has the following advantages:
1. the invention provides a method for prejudging the fault of an industrial automatic control system, which greatly reduces the downtime of the industrial automatic production process, improves the production efficiency, and reduces the economic loss and the waste of industrial raw materials caused by the fault of the system;
2. according to the method, the cloud platform is used as simulation and decision-making auxiliary computing resources, a user can customize the computing capacity of the cloud platform according to the requirements of different industrial control systems, and the waste of time, resources and energy consumption in the simulation process is greatly reduced;
3. the super real-time simulation technology provided by the invention uses the controller and the code which are the same as the actual situation, so that the time for establishing a simulation model is saved, the time for developing and testing the system is greatly saved, and the simulation efficiency is improved.
4. The super real-time simulation technology provided by the invention achieves the effect of prejudging the system fault in advance by combining the means of closed-loop super real-time simulation and online real-time verification of the industrial controller and the virtual controller.
The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of the decision method of the present invention;
FIG. 2 is a schematic structural diagram of a preferred embodiment of a decision method related system of the present invention;
fig. 3 is a schematic diagram of the working relationship between the cloud super real-time simulation platform and other modules in the preferred embodiment of the decision method of the present invention.
Detailed Description
The following describes in detail a preferred embodiment of a cloud-based super-real-time simulation platform and hardware-in-the-loop real-time decision method according to the present invention with reference to the accompanying drawings, but the present invention is not limited to this embodiment. In the following description of the preferred embodiments of the present invention, specific details are set forth in order to provide a thorough understanding of the present invention.
Example 1
As shown in fig. 1, a cloud super real-time simulation platform and hardware-in-the-loop based real-time decision method includes the following steps:
As shown in fig. 2, a system of a real-time decision method based on a cloud super real-time simulation platform and a hardware-in-loop includes the cloud super real-time simulation platform, sensors and actuators, an industrial controller and an industrial system device, the cloud super real-time simulation platform is connected with at least one industrial controller through an industrial ethernet, each industrial controller is connected with at least one sensor and at least one actuator through an industrial field bus, and the at least one sensor and the at least one actuator are connected to the industrial system device. As shown in fig. 2, the system includes 3 sensors and 3 actuators, 3 industrial controllers. The industrial field bus updates the connected input devices and output devices at a fixed frequency, and when each cycle period begins, the first controller or the second controller performs logic calculation according to all input values read by the industrial field bus, updates the output values of the first controller or the second controller bus and transmits the output values to the actuator.
As shown in fig. 3, the cloud super real-time simulation platform includes a communication module, a virtual controller operation stack and a decision-making auxiliary manager, where the communication module reads an input value through an industrial field bus, a sensor and an actuator, and writes the input value into the virtual controller operation stack; the virtual controller operation stack comprises one or more virtual controller operation environments, each virtual controller operation environment operates independently, and after the input value is processed, the virtual controller pushes the generated second output variable value to the decision auxiliary manager; and the decision auxiliary manager compares the received second output variable value with fault tree data preset in a cloud super real-time simulation platform database, judges whether a fault occurs according to a comparison result, searches a solution of the corresponding fault from the database and writes the solution back to the industrial controller, and thus, the fault pre-judgment and self-protection functions are realized.
When the system starts to deploy the industrial automation control program, the control codes are uploaded to the industrial controller and the virtual controller simultaneously.
Hardware-in-Loop, i.e. Hardware-in-the-Loop, is divided into the following three cases (if the simulation of the real controller is called as the virtual controller and the simulation of the real object is called as the virtual object, 3 types of simulation of the control system can be obtained:)
Firstly, a virtual controller and a virtual object are a dynamic simulation system, and are pure system simulation;
a virtual controller and an actual object are a Rapid Control Prototype (RCP) simulation system, and the system is a semi-physical simulation system;
and the other type of hardware-in-loop (HiL) simulation system is the other type of semi-physical simulation of the system.
Example 2
Embodiment 2 adopts a method and a system similar to those of embodiment 1, wherein only the cloud server adopted by the super real-time simulation computing is replaced by the local server, and the network delay can be reduced by using the local server, but the relative computing capacity of the local server is weaker than that of the cloud server.
Example 3
Embodiment 3 adopts a method and a system similar to those in embodiment 1, wherein the fault tree can be replaced by a fault defined by any custom-formatted text or data, but after the fault defined by any custom-formatted text or data is replaced, the system cannot share information, which causes difficulty in sharing and mining output data.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations can be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions that can be obtained by a person skilled in the art through logic analysis, reasoning or limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection determined by the claims.
Claims (9)
1. A real-time decision method based on a cloud super real-time simulation platform and a hardware-in-the-loop is characterized by comprising the following steps:
reading an input value;
writing the input value read in the step (100) into an input variable memory of the first controller and an input variable memory of the second controller in a step (200);
step (300) according to the input value written in step (200), the first controller executes the operation logic to obtain a first output variable value, and the second controller executes the operation logic to obtain a second output variable value;
step (400) comparing the second output variable value obtained in step (300) with a fault tree;
step (410) according to the comparison result of step (400), judging whether a fault exists: if there is a failure, proceeding to step (500), if there is no failure, proceeding to step (600);
step (500) of forcibly writing a third output variable value into the first controller according to the judgment result in step (410), and proceeding to step (600);
step (600) of comparing the first output variable value with the second output variable value according to step (410) or comparing the third output variable value with the second output variable value according to step (500);
step (610) of determining whether the first output variable value and the second output variable value in step (600) are the same or whether the third output variable value and the second output variable value are the same: if the first output variable value is the same as the second output variable value or the third output variable value is the same as the second output variable value, returning to step (100); if the first output variable value is different from the second output variable value or the third output variable value is different from the second output variable value, entering step (700);
step (700) according to the judgment result of step (610), if the first output variable value is different from the second output variable value, copying the first output variable value to the second controller, and transmitting the first output variable value to the actuator, and returning to step (100); copying the third output variable value into the second controller and delivering the third output variable value to an actuator if the third output variable value is different from the second output variable value, returning to step (100);
the first controller is an industrial controller, the second controller is a virtual controller, and the second controller is a virtual controller mirror image established by a cloud super real-time simulation platform for the first controller.
2. The cloud-based hyper-real-time simulation platform and hardware-in-the-loop real-time decision method according to claim 1, wherein the input values in the step (100) are all input values read through an industrial field bus, and the first controller and the second controller read the input values at the same time.
3. The cloud-based super real-time simulation platform and hardware-in-the-loop real-time decision method as claimed in claim 2, wherein the first controller and the second controller simultaneously establish a closed-loop connection with an input device, and the first controller and the second controller periodically read the input value.
4. The cloud-based super real-time simulation platform and hardware-in-the-loop real-time decision method according to claim 1, wherein the operation logic in the step (300) is an actual working logic of the first controller, and the second controller simulates one or more next update cycles by using the operation logic according to the input values.
5. The cloud-based hyper-real-time simulation platform and hardware-in-the-loop real-time decision method as claimed in claim 1, wherein said fault in said step (410) comprises a problem causing system shutdown, process shutdown.
6. The cloud super real-time simulation platform and hardware-in-the-loop based real-time decision method as claimed in claim 5, wherein the writing of the third output variable value to the first controller in the step (500) is performed in real time by the cloud super real-time simulation platform sending a force rewrite instruction to the first controller.
7. The cloud-based hyper-real-time simulation platform and hardware-in-the-loop real-time decision method according to any one of claims 1 to 6, wherein the decision method is based on a system comprising a cloud hyper-real-time simulation platform, a sensor and an actuator, an industrial controller and an industrial system device, wherein the cloud hyper-real-time simulation platform and the industrial controller are connected through an industrial Ethernet network, the industrial controller and the sensor and the actuator are connected through an industrial field bus, and the sensor and the actuator are connected to the industrial system device.
8. The cloud super real-time simulation platform and hardware-in-the-loop based real-time decision method as claimed in claim 7, wherein the cloud super real-time simulation platform comprises a communication module, a virtual controller operation stack and a decision auxiliary manager, wherein the communication module reads input values through an industrial field bus, a sensor and an actuator and writes the input values into the virtual controller operation stack; the virtual controller operation stack comprises one or more virtual controller operation environments, each virtual controller operation environment operates independently, and after the input value is processed, the virtual controller pushes the generated second output variable value to the decision auxiliary manager; and the decision auxiliary manager compares the received second output variable value with fault tree data preset in a cloud super real-time simulation platform database, judges whether a fault occurs according to a comparison result, searches a solution of the corresponding fault from the database and writes the solution back to the industrial controller.
9. The cloud-based super real-time simulation platform and hardware-in-the-loop real-time decision method as claimed in claim 8, wherein when the system starts to deploy an industrial automation control program, control code will be uploaded to the industrial controller and the virtual controller simultaneously.
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| EP3660612B1 (en) * | 2018-11-30 | 2022-12-28 | Siemens Aktiengesellschaft | Method and system for elimination of fault conditions in a technical installation |
| CN110648040A (en) * | 2019-06-17 | 2020-01-03 | 河北人元科技有限公司 | Data processing system and working method thereof |
| CN112306033B (en) * | 2019-07-29 | 2022-01-28 | 北京新能源汽车股份有限公司 | Vehicle-mounted controller joint test control method, device and system |
| CN110751873B (en) * | 2019-11-15 | 2021-10-26 | 郑州意昂新能源汽车科技有限公司 | Method for interconnecting whole vehicle electric control practical training platform of new energy automobile and actual vehicle |
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