Control prediction method and device based on multi-source heterogeneous integrated simulation

Abstract

The invention provides a control prediction method and device based on multi-source heterogeneous integrated simulation, and relates to the technical field of model prediction control. When the method is executed, firstly, a plurality of subsystem models are constructed according to the complex system, the subsystem models are multi-source heterogeneous models, then, the subsystem models are integrated through the multi-source heterogeneous technology to obtain a refined digital prototype, and finally, operation data of the complex system are input into the refined digital prototype. And obtaining a predicted value of the complex system. Therefore, a plurality of subsystem models are integrated by using a multi-source heterogeneous technology to obtain a refined digital prototype, and the refined digital prototype can be used for accurately performing control prediction on a complex system. Therefore, the accuracy of control prediction of the complex model can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of model predictive control, and in particular to a control prediction method and device based on multi-source heterogeneous integrated simulation. Background Art

[0002] Model predictive control is an advanced control strategy that uses predictive models, rolling optimization and feedback correction to achieve precise control of the system. In traditional model predictive control methods, the prediction model is generally constructed using a single modeling tool with existing technology. The constructed prediction model is relatively simple and the prediction result is of low accuracy.

[0003] In summary, how to improve the accuracy of control prediction of complex models is an urgent problem that technical personnel in this field need to solve. Summary of the invention

[0004] In view of this, the present application provides a control prediction method and device based on multi-source heterogeneous integrated simulation, aiming to improve the accuracy of control prediction of complex models.

[0005] In a first aspect, the present application provides a control prediction method based on multi-source heterogeneous integrated simulation, comprising:

[0006] Construct multiple subsystem models according to the complex system; the multiple subsystem models are multi-source heterogeneous models;

[0007] Integrate the multiple subsystem models using multi-source heterogeneous technology to obtain a refined digital prototype;

[0008] The operating data of the complex system is input into the refined digital prototype to obtain the predicted value of the complex system.

[0009] Optionally, constructing multiple subsystem models according to the complex system includes:

[0010] Analyzing the multiple subsystems constituting the complex system to obtain characteristics of the multiple subsystems;

[0011] According to the characteristics of the multiple subsystems, the multiple subsystems are modeled respectively using different modeling tools to obtain the multiple subsystem models.

[0012] Optionally, the integrating the multiple subsystem models by using multi-source heterogeneous technology to obtain a refined digital prototype includes:

[0013] Based on a unified interface standard, the multiple subsystem models are processed respectively to obtain multiple processed subsystem models;

[0014] Build interface models;

[0015] A refined digital prototype is constructed based on the multiple processed subsystem models and the interface model.

[0016] Optionally, the constructing the interface model includes:

[0017] Constructing the interface model according to each bus communication mechanism and the preset communication protocol of the complex system;

[0018] A mapping relationship between the interface model and the multiple subsystem models is established.

[0019] Optionally, constructing a refined digital prototype according to the multiple processed subsystem models and the interface model includes:

[0020] Associating the subsystem model with the interface model according to the mapping relationships between the interface model and the plurality of subsystem models respectively;

[0021] The interface models are connected to construct the refined digital prototype.

[0022] Optionally, inputting the operating data of the complex system into the refined digital prototype to obtain a predicted value of the complex system includes:

[0023] Determining the operating data of the complex system as the current moment input of the refined digital prototype;

[0024] Using the refined digital prototype to perform ultra-real-time prediction time limit prediction and solution on the current moment input until the number of running beats meets the prediction time limit requirement;

[0025] The solved data of the last beat is determined as the predicted value of the complex system.

[0026] Optionally, after obtaining the predicted value of the complex system, the method further includes:

[0027] A control target of the complex system is adjusted according to the predicted value of the complex system.

[0028] In a second aspect, the present application provides a control prediction device based on multi-source heterogeneous integrated simulation, comprising:

[0029] A construction module, used to construct multiple subsystem models according to a complex system; the multiple subsystem models are multi-source heterogeneous models;

[0030] An integration module, used to integrate the multiple subsystem models using multi-source heterogeneous technology to obtain a refined digital prototype;

[0031] The prediction module is used to input the operating data of the complex system into the refined digital prototype to obtain the predicted value of the complex system.

[0032] Optionally, the building block includes:

[0033] An analysis submodule, used for analyzing the multiple subsystems constituting the complex system to obtain the characteristics of the multiple subsystems;

[0034] The first construction submodule is used to model the multiple subsystems respectively using different modeling tools according to the characteristics of the multiple subsystems to obtain the multiple subsystem models.

[0035] Optionally, the integrated module includes:

[0036] A processing submodule, used for processing the multiple subsystem models respectively based on a unified interface standard to obtain multiple processed subsystem models;

[0037] The second construction submodule is used to construct an interface model;

[0038] The third construction submodule is used to construct a refined digital prototype according to the multiple processed subsystem models and the interface model.

[0039] Optionally, the second construction submodule includes:

[0040] A construction unit, used to construct the interface model according to each bus communication mechanism and a communication protocol preset by the complex system;

[0041] An establishing unit is used to establish mapping relationships between the interface model and the multiple subsystem models respectively.

[0042] Optionally, the third construction submodule includes:

[0043] an associating unit, configured to associate the subsystem model with the interface model according to mapping relationships between the interface model and the plurality of subsystem models respectively;

[0044] A connection unit is used to connect the interface model to construct the refined digital prototype.

[0045] Optionally, the prediction module includes:

[0046] A first determining subunit, configured to determine the operation data of the complex system as the current moment input of the refined digital prototype;

[0047] A prediction and solution subunit, used for using the refined digital prototype to perform super real-time prediction and solution on the current input until the running beat number meets the prediction time limit requirement;

[0048] The solved data of the last beat is determined as the predicted value of the complex system.

[0049] Optionally, the device further comprises:

[0050] The control target adjustment module is used to adjust the control target of the complex system according to the predicted value of the complex system.

[0051] In a third aspect, an embodiment of the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the control prediction method based on multi-source heterogeneous integrated simulation as described in any one of the implementation methods in the first aspect of the embodiment of the present application.

[0052] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a terminal device, the terminal device executes a control prediction method based on multi-source heterogeneous integrated simulation as described in any one of the implementation methods in the first aspect of the embodiment of the present application.

[0053] The present application provides a control prediction method based on multi-source heterogeneous integrated simulation. When executing the method, multiple subsystem models are first constructed according to the complex system, wherein the multiple subsystem models are multi-source heterogeneous models. Then, the aforementioned multiple subsystem models are integrated using multi-source heterogeneous technology to obtain a refined digital prototype. Finally, the operation data of the complex system is input into the refined digital prototype to obtain the predicted value of the complex system. In this way, multiple subsystem models are integrated using multi-source heterogeneous technology to obtain a refined digital prototype, and the refined digital prototype can be used to accurately predict the control of the complex system. In this way, the accuracy of the control prediction of the complex model can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 A flowchart of a control prediction method based on multi-source heterogeneous integrated simulation provided in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of processing each subsystem model provided in an embodiment of the present application;

[0057] Figure 3 A schematic diagram of the structure of a control prediction device based on multi-source heterogeneous integrated simulation provided in an embodiment of the present application;

[0058] Figure 4 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. The present application provides a control prediction method and device based on multi-source heterogeneous integrated simulation, which is used in the field of model predictive control technology. The above is only an example and does not limit the application field of the method and device name provided in the present application.

[0060] Model predictive control is an advanced control strategy that uses predictive models, rolling optimization and feedback correction to achieve precise control of the system. In traditional model predictive control methods, the prediction model is generally constructed using a single modeling tool with existing technology. The constructed prediction model is relatively simple and the prediction result is of low accuracy.

[0061] After research, the inventor proposed the technical solution of this application. First, multiple subsystem models are constructed according to the complex system, wherein the multiple subsystem models are multi-source heterogeneous models. Then, the aforementioned multiple subsystem models are integrated using multi-source heterogeneous technology to obtain a refined digital prototype. Finally, the operation data of the complex system is input into the refined digital prototype to obtain the predicted value of the complex system. In this way, multiple subsystem models are integrated using multi-source heterogeneous technology to obtain a refined digital prototype, which can be used to accurately predict the control of the complex system. In this way, the accuracy of the control prediction of the complex model can be improved.

[0062] In order to enable those skilled in the art to better understand the present application, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application. It should be noted that, for ease of description, only the parts related to the relevant invention are shown in the accompanying drawings. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0063] See also Figure 1 , Figure 1A flowchart of a control prediction method based on multi-source heterogeneous integrated simulation provided in an embodiment of the present application includes:

[0064] S101: Construct multiple subsystem models based on complex systems.

[0065] For complex systems, we first need to analyze the characteristics of each subsystem that makes up the complex system, and select appropriate modeling tools in the field to build models for each subsystem. This ensures that each subsystem model can accurately reflect the actual situation of each subsystem.

[0066] S102: Integrate multiple subsystem models using multi-source heterogeneous technology to obtain a refined digital prototype.

[0067] By utilizing multi-source heterogeneous integration technology, the subsystem models of the complex system are integrated to build a comprehensive and refined digital prototype that can truly reflect the physical characteristics and dynamic behavior of the complex system and provide a basis for subsequent prediction and control.

[0068] Specifically, Figure 2 As shown, Figure 2 A schematic diagram for processing each subsystem model provided in the embodiment of the present application, based on a unified interface standard, performs interface sorting, conversion process design planning, and conversion tool design and implementation for multi-domain and multi-modeling platform models, and processes each subsystem model of a complex system into a model unit that can be imported and integrated based on a unified platform, that is, multiple processed subsystem models.

[0069] Next, it is necessary to construct the interface model, that is, to construct bus interface models such as 1553B, 422, CAN and network interface models such as optical fiber and Ethernet to support data interaction between subsystem models of complex systems and between digital prototypes and physical objects. Specifically, it is necessary to continue to build the interface model according to the communication mechanisms of each bus and the communication protocols agreed upon in the complex system application engineering, and then establish the mapping relationship between the interface model and each subsystem model, and between the interface model and the physical interface of the communication board through description file association and other methods.

[0070] Finally, the subsystem model is associated with the interface model. By connecting the interface model, the data interaction channel between the subsystems is established, and the construction of the digital prototype of the complex system is completed. Specifically, it is necessary to firstly represent the association relationship between the subsystem model and the interface model, and the correspondence between the input and output interface of the subsystem model and the interface model signal in a graphical manner on the operation interface, and record the above relationship in a description file for engineering scheduling. Then, the connection relationship of the interface model, that is, the interaction relationship between the subsystems, is represented in a graphical manner on the operation interface, and the above relationship is recorded in a description file for engineering scheduling. In this way, a refined digital prototype can be obtained.

[0071] S103: Inputting the operation data of the complex system into the refined digital prototype to obtain the predicted value of the complex system.

[0072] Based on the refined digital prototype, the prediction logic is designed, and the system data is collected in real time through the virtual and real data interaction interface, and input into the digital prototype for prediction. At the same time, the scheduling and execution of the prototype project is reasonably planned to ensure the efficiency and accuracy of the prediction process.

[0073] Prediction logic design and its scheduling execution include the following four core steps:

[0074] (1) Real-time collection of entity operation data

[0075] The bus and network interface models constructed during the prototype engineering construction phase can support data interaction between digital prototypes and physical objects. The prediction logic script schedules the prototype engineering to execute physical data collection through the prototype engineering scheduling interface, such as the API interface, and collects entity operation data in real time.

[0076] (2) Schedule the prototype project and assign the actual sampled data to the prototype project as the initial value for the solution.

[0077] (3) Super real-time operation, each scheduling operation is 10 beats (assuming the prediction time limit is 10s, for example, the prediction time limit is 10s, the simulation step size is 1s, then the operation is 10 beats)

[0078] After the prototype project is built, it is configured and ultra-real-time simulation is set. During the time it takes to predict the logic script to run for 1 beat, the prototype project uses the collected entity running data as the initial running value and runs for 10 beats, that is, predicting the running status of the prototype after 10 beats.

[0079] (4) Feedback the last beat data as the prediction value

[0080] After obtaining the predicted value, the predicted value is compared and analyzed with the expected target, and the control target of the complex system is adjusted in real time. Through rolling optimization and feedback correction mechanism, the control strategy is continuously optimized to ensure that the system can operate in the expected way and achieve the goal of predictive control.

[0081] In the embodiment provided in the present application, multiple subsystem models are first constructed according to the complex system, wherein the multiple subsystem models are multi-source heterogeneous models, and then the aforementioned multiple subsystem models are integrated using multi-source heterogeneous technology to obtain a refined digital prototype, and finally, the operation data of the complex system is input into the refined digital prototype to obtain the predicted value of the complex system. In this way, multiple subsystem models are integrated using multi-source heterogeneous technology to obtain a refined digital prototype, and the refined digital prototype can be used to accurately predict the control of the complex system. In this way, the accuracy of the control prediction of the complex model can be improved.

[0082] The above are some specific implementations of the control prediction method based on multi-source heterogeneous integrated simulation provided by the embodiments of the present application. Based on this, the present application also provides a corresponding device. The device provided by the embodiments of the present application will be introduced from the perspective of functional modularization.

[0083] See also Figure 3 , Figure 3 A schematic diagram of the structure of a control prediction device based on multi-source heterogeneous integrated simulation provided in an embodiment of the present application, the control prediction device 300 based on multi-source heterogeneous integrated simulation includes:

[0084] A construction module 310 is used to construct multiple subsystem models according to a complex system; the multiple subsystem models are multi-source heterogeneous models;

[0085] An integration module 320, for integrating the plurality of subsystem models using multi-source heterogeneous technology to obtain a refined digital prototype;

[0086] The prediction module 330 is used to input the operating data of the complex system into the refined digital prototype to obtain the predicted value of the complex system.

[0087] Optionally, the construction module 310 includes:

[0088] An analysis submodule, used for analyzing the multiple subsystems constituting the complex system to obtain the characteristics of the multiple subsystems;

[0089] The first construction submodule is used to model the multiple subsystems respectively using different modeling tools according to the characteristics of the multiple subsystems to obtain the multiple subsystem models.

[0090] Optionally, the integration module 320 includes:

[0091] A processing submodule, used for processing the multiple subsystem models respectively based on a unified interface standard to obtain multiple processed subsystem models;

[0092] The second construction submodule is used to construct an interface model;

[0093] The third construction submodule is used to construct a refined digital prototype according to the multiple processed subsystem models and the interface model.

[0094] Optionally, the second construction submodule includes:

[0095] A construction unit, used to construct the interface model according to each bus communication mechanism and a communication protocol preset by the complex system;

[0096] An establishing unit is used to establish mapping relationships between the interface model and the multiple subsystem models respectively.

[0097] Optionally, the third construction submodule includes:

[0098] an associating unit, configured to associate the subsystem model with the interface model according to mapping relationships between the interface model and the plurality of subsystem models respectively;

[0099] A connection unit is used to connect the interface model to construct the refined digital prototype.

[0100] Optionally, the prediction module 330 includes:

[0101] A first determining subunit, configured to determine the operation data of the complex system as the current moment input of the refined digital prototype;

[0102] A prediction and solution subunit, used for using the refined digital prototype to perform super real-time prediction and solution on the current input until the running beat number meets the prediction time limit requirement;

[0103] The solved data of the last beat is determined as the predicted value of the complex system.

[0104] Optionally, the device 300 further includes:

[0105] The control target adjustment module is used to adjust the control target of the complex system according to the predicted value of the complex system.

[0106] The embodiments of the present application also provide corresponding devices and computer storage media for implementing the solutions provided by the embodiments of the present application.

[0107] like Figure 4 As shown, the computer device 01 is in the form of a general computing device. The components of the computer device 01 may include but are not limited to: one or more processors or processing units 03, a system memory 08, and a bus 04 connecting different system components (including the system memory 08 and the processing unit 03).

[0108] Bus 04 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor or a local bus using any of a variety of bus structures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnect (PCI) bus.

[0109] The computer device 01 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 01, including volatile and non-volatile media, removable and non-removable media.

[0110] The system memory 08 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 09 and / or cache memory 10. The computer device 01 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 11 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4 Not shown in the figure, a disk drive for reading and writing a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 04 via one or more data medium interfaces. The memory 08 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0111] A program / utility 12 having a set (at least one) of program modules 13 may be stored, for example, in the memory 08, such program modules 13 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination thereof may include an implementation of a network environment. The program modules 13 generally perform the functions and / or methods of the embodiments described herein.

[0112] The computer device 01 may also communicate with one or more external devices 02 (e.g., keyboard, pointing device, display 07, etc.), one or more devices that enable a user to interact with the computer device 01, and / or any device that enables the computer device 01 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed via input / output (I / O) interface 06. Furthermore, the computer device 01 may also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN) and / or public network, such as the Internet) via network adapter 05. Figure 4 As shown, the network adapter 05 communicates with other modules of the computer device 01 via the bus 04. It should be understood that although Figure 4 Not shown, other hardware and / or software modules may be used in conjunction with computer device 01, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0113] The processor unit 03 executes various functional applications and data processing by running programs stored in the system memory 08, for example, implementing a control prediction method based on multi-source heterogeneous integrated simulation provided in an embodiment of the present application.

[0114] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0115] Through the description of the above implementation methods, it can be known that those skilled in the art can clearly understand that all or part of the steps in the above-mentioned embodiment method can be implemented by means of software plus a general hardware platform. Based on such an understanding, the technical solution of the present application can be embodied in the form of a software product, which can be stored in a storage medium, such as a read-only memory (ROM) / RAM, a magnetic disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network communication device such as a router) to execute the methods described in each embodiment of the present application or some parts of the embodiments.

[0116] Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative work.

[0117] The above description is merely an exemplary embodiment of the present application and is not intended to limit the protection scope of the present application.

Claims

1. A control prediction method based on multi-source heterogeneous integrated simulation, characterized in that: include: Construct multiple subsystem models according to the complex system; the multiple subsystem models are multi-source heterogeneous models; Integrate the multiple subsystem models using multi-source heterogeneous technology to obtain a refined digital prototype; The operating data of the complex system is input into the refined digital prototype to obtain the predicted value of the complex system.

2. The method according to claim 1, characterized in that The method of constructing multiple subsystem models according to the complex system includes: Analyzing the multiple subsystems constituting the complex system to obtain characteristics of the multiple subsystems; According to the characteristics of the multiple subsystems, the multiple subsystems are modeled respectively using different modeling tools to obtain the multiple subsystem models.

3. The method according to claim 1, characterized in that The method of integrating the multiple subsystem models by using multi-source heterogeneous technology to obtain a refined digital prototype includes: Based on a unified interface standard, the multiple subsystem models are processed respectively to obtain multiple processed subsystem models; Build interface models; A refined digital prototype is constructed based on the multiple processed subsystem models and the interface model.

4. The method according to claim 3, characterized in that The construction of the interface model includes: Constructing the interface model according to each bus communication mechanism and the preset communication protocol of the complex system; A mapping relationship between the interface model and the multiple subsystem models is established.

5. The method according to claim 4, characterized in that The step of constructing a refined digital prototype according to the plurality of processed subsystem models and the interface model comprises: Associating the subsystem model with the interface model according to the mapping relationships between the interface model and the plurality of subsystem models respectively; The interface models are connected to construct the refined digital prototype.

6. The method according to claim 1, characterized in that The step of inputting the operating data of the complex system into the refined digital prototype to obtain the predicted value of the complex system includes: Determining the operating data of the complex system as the current moment input of the refined digital prototype; Using the refined digital prototype to perform ultra-real-time prediction time limit prediction and solution on the current moment input until the number of running beats meets the prediction time limit requirement; The solved data of the last beat is determined as the predicted value of the complex system.

7. The method according to any one of claims 1 to 6, characterized in that: After obtaining the predicted value of the complex system, the method further includes: A control target of the complex system is adjusted according to the predicted value of the complex system.

8. A control prediction device based on multi-source heterogeneous integrated simulation, characterized in that: include: A construction module, used to construct multiple subsystem models according to a complex system; the multiple subsystem models are multi-source heterogeneous models; An integration module, used to integrate the multiple subsystem models using multi-source heterogeneous technology to obtain a refined digital prototype; The prediction module is used to input the operating data of the complex system into the refined digital prototype to obtain the predicted value of the complex system.

9. A computer device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the control prediction method based on multi-source heterogeneous integrated simulation as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device executes the control prediction method based on multi-source heterogeneous integrated simulation as described in any one of claims 1 to 7.

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