Integrated method for supporting design and optimization of complex system
Through an integrated method that supports complex system design and optimization, using preset graphics and text modeling frameworks and intelligent optimization algorithms, the system design, simulation and optimization of complex systems are unified, and the complexity in the existing technology is solved The problem of difficult to unify system model design and optimization has improved R&D efficiency.
Patent Information
- Application Number
- CN202411366834.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-29
- Publication Date
- 2024-12-27
AI Technical Summary
The existing technology cannot unify the design modeling, simulation modeling and optimization modeling of complex systems, resulting in modeling personnel needing to learn multiple languages and platforms, increasing learning costs, and cross-language and cross-platform implementation methods lead to models. The design process is complex and consistency is not guaranteed.
Adopting an integrated method that supports complex system design and optimization, the preset graphic and text modeling framework is divided into problem domain, verification domain and optimization domain, and requirements analysis, functional verification, physical architecture model establishment and multidisciplinary Optimize model construction, use intelligent optimization algorithm to iteratively solve to obtain the best optimization solution, and realize automatic verification of system design.
The seamless integration of system design, simulation and optimization of complex system models is achieved, the efficiency of the R&D process is improved, the problem of difficulty in seamless integration of system optimization with design and simulation is avoided, and the barriers between models at each stage are broken.
Smart Images
Figure CN119203769A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of system modeling, and more particularly to an integrated method for supporting complex system design and optimization. Background Art
[0002] With the continuous improvement of science and technology and demand, especially in the military and manufacturing fields, the complexity of research objects is gradually increasing. The traditional document-based system engineering method has brought great difficulties and challenges to modelers. With the rapid development of computer technology, model-based system engineering (MBSE) has gradually become a mainstream method for complex systems and even systems in the field of system design and simulation modeling. The model-based R&D model has many advantages such as reusability, unambiguity, easy to understand, and easy to reuse. At present, the mainstream modeling language of MBSE is the system modeling language SysML (System Modeling Language). It is the preferred solution to unify the full process modeling of complex systems from demand analysis to system design, system simulation and system optimization based on SysML.
[0003] At present, the main method for full-process modeling of complex systems is: first, complete the requirements and system design modeling of complex systems through the 9 diagrams provided by SysML (requirement diagram, module definition diagram, internal connection diagram, state machine diagram, etc.), and then re-model and simulate through other simulation modeling languages such as modelica, matlab / simulink, etc., and then combine optimization software such as Isight, ModelCenter, etc. to achieve system optimization.
[0004] At present, the full-process modeling method for complex systems cannot unify the design modeling, simulation modeling and optimization modeling of complex systems, and needs to be implemented through different modeling languages and platforms. This greatly increases the learning cost of modelers. In addition, the cross-language and cross-platform implementation method makes it difficult to change the design process of complex system models and cannot ensure consistency. Summary of the invention
[0005] In view of this, the present invention provides an integrated method for supporting complex system design and optimization to solve the problems in the background technology.
[0006] In order to achieve the above object, the present invention adopts the following technical solution:
[0007] An integrated approach to supporting complex system design and optimization, including:
[0008] Divide the model hierarchy into problem domain, solution domain, verification domain and optimization domain according to modeling requirements;
[0009] Selecting a preset first graphic model framework and a first text model framework that are consistent with the metamodel in the problem domain to sequentially complete the system's requirement analysis, function analysis, and logical architecture model establishment;
[0010] In the verification domain, the preset XLab interpreter and simulator automatically generate a logical simulation model oriented to functional requirements to implement functional requirement verification and provide guidance for the physical architecture model;
[0011] Selecting a preset second graphic model framework and a second text model framework that are consistent with the metamodel in the solution domain to establish a physical architecture model of the system;
[0012] In the verification domain, select the preset XLab interpreter and simulator to automatically generate an integrated simulation model for functional and non-functional requirements;
[0013] A third graphical model framework and a third text model framework that are preset and consistent with the metamodel are selected in the optimization domain to establish a multidisciplinary optimization model, wherein the multidisciplinary optimization model is used to describe a multidisciplinary optimization object model of a complex system; and a binding is established with the output values of the subsystem parameters and the objective function-related variables preset in the physical architecture model in the solution domain;
[0014] The best optimization solution obtained based on intelligent optimization algorithms such as the multi-objective genetic algorithm NSGA2 is automatically fed back to the system design model through the optimization domain to achieve automatic verification of top-level requirements.
[0015] Preferably, in the above-mentioned integrated method for supporting complex system design and optimization, the logical architecture model includes:
[0016] Requirement model framework, use case model framework, activity model framework, coupling model framework, discrete model framework, among which:
[0017] The requirement model framework is used to describe the needs of stakeholders, system design requirements, and the relationship between the two requirements;
[0018] The use case model framework is used to describe the functional scenarios of complex systems;
[0019] The activity model framework is used to describe the functional activity sequence that realizes the functional scenario of complex systems;
[0020] The coupled model framework is used to describe models in complex systems that are composed of atomic models or other coupled model components;
[0021] The discrete class model framework is used to describe indivisible models with discrete behaviors in complex systems.
[0022] Preferably, in the above-mentioned integrated method for supporting complex system design and optimization, the graphical model framework includes:
[0023] Requirements graphical modeling framework, use case graphical modeling framework, activity graphical modeling framework, coupling class graphical modeling framework, discrete class graphical modeling framework, among which:
[0024] The demand graph modeling framework consists of preset demand graphs;
[0025] The use case graphical modeling framework consists of preset use case diagrams;
[0026] The activity graph modeling framework consists of preset activity graphs;
[0027] The coupled graphical modeling framework is composed of a combination of preset definition graphs and connection graphs;
[0028] The discrete class graphical modeling framework consists of a combination of preset definition diagrams and state machine diagrams;
[0029] The requirement diagram is used to describe stakeholders, stakeholder needs, system design requirements, and the relationship between the requirements;
[0030] The use case diagram is used to describe the system, the use cases of the system, the participants and the relationship between the three;
[0031] The activity diagram is used to describe the functional activity interaction between the system and external units or the subsystems within the system;
[0032] The definition diagram is used to describe the component parameters, state variables and input and output port types of the system graphical model framework;
[0033] The connection diagram is used to describe the connection relationship between components of the coupling type graphic model;
[0034] The state machine diagram is used to describe the behavior constraint relationship represented by the transition constraints between different states of the discrete class graphic model.
[0035] Preferably, in the above-mentioned integrated method for supporting complex system design and optimization, the text model framework includes:
[0036] Requirement text modeling framework, use case text modeling framework, activity text modeling framework, coupling text modeling framework, discrete text modeling framework, among which:
[0037] The requirement text modeling framework consists of preset requirement texts;
[0038] The use case text modeling framework consists of preset use case texts;
[0039] The active text modeling framework consists of preset active text domains;
[0040] The coupled text modeling framework is composed of a combination of preset definition text and connection text;
[0041] The discrete class text modeling framework is composed of a combination of preset definition text and state machine text;
[0042] The requirement text is used to describe stakeholders, stakeholder needs, system design requirements, and the relationship between the three requirements;
[0043] The use case text is used to describe the system, the use cases of the system, the participants, and the relationship between the three;
[0044] The definition text is used to describe the component parameters, state variables and input and output port types of the system text model;
[0045] The connection text is used to describe the connection relationship between components of the coupling class text model;
[0046] The state machine text is used to describe the behavior constraint relationship represented by the transition constraints between different states of the discrete class text model.
[0047] Preferably, in the above-mentioned integrated method for supporting complex system design and optimization, the physical architecture model framework includes:
[0048] Coupling model framework, continuous model framework, discrete model framework, among which:
[0049] The coupled model framework is used to describe models in complex systems that are composed of atomic models or other coupled model components;
[0050] The continuous model framework is used to describe indivisible models with continuous behaviors in complex systems;
[0051] The discrete class model framework is used to describe indivisible models with discrete behaviors in complex systems.
[0052] Preferably, in the above-mentioned integrated method for supporting complex system design and optimization, the second graphical model framework includes:
[0053] Coupled graphics modeling framework, continuous graphics modeling framework, discrete graphics modeling framework, among which:
[0054] The coupled graphical modeling framework is composed of a combination of preset definition graphs and connection graphs;
[0055] The continuous class graphical modeling framework is composed of a combination of preset definition graphs and equation graphs;
[0056] The discrete class graphical modeling framework consists of a combination of preset definition diagrams and state machine diagrams;
[0057] The definition diagram is used to describe the component parameters, state variables and input and output port types of the system graphical model framework;
[0058] The connection diagram is used to describe the connection relationship between components of the coupling type graphic model;
[0059] The equation graph is used to describe the behavior constraint relationship represented by the ordinary differential / algebraic differential equation group in the continuous class graphical model;
[0060] The state machine diagram is used to describe the behavior constraint relationship represented by the transition constraints between different states of the continuous class graphic model.
[0061] Preferably, in the above-mentioned integrated method for supporting complex system design and optimization, the second text model framework includes:
[0062] The second text model framework includes:
[0063] Coupled text modeling framework, continuous text modeling framework, discrete text modeling framework, among which:
[0064] The coupled text modeling framework is composed of a combination of preset definition text and connection text;
[0065] The continuous text modeling framework is composed of a combination of preset definition text and equation text;
[0066] The discrete class text modeling framework is composed of a combination of preset definition text and state machine text;
[0067] The definition text is used to describe the component parameters, state variables and input and output port types of various models;
[0068] The connection text is used to describe the connection relationship between the components of the coupling model;
[0069] The equation text is used to describe the behavior constraint relationship represented by the ordinary differential / algebraic differential equation group in the continuous text model;
[0070] The state machine text is used to describe the behavior constraint relationship represented by the transition constraints between different states of the discrete class text model.
[0071] Preferably, in the above-mentioned integrated method for supporting complex system design and optimization, the third graphical model framework includes: a multidisciplinary optimization graphical model framework, wherein:
[0072] The multidisciplinary optimization graphic model framework is composed of a preset definition diagram; the definition diagram is used to describe the design variables, design constraints and optimization objectives in the multidisciplinary optimization graphic model.
[0073] Preferably, in the above-mentioned integrated method for supporting complex system design and optimization, the third text model framework includes: a multidisciplinary optimization text model framework, wherein:
[0074] The multidisciplinary optimization text model framework is composed of preset definition texts; the definition texts are used to describe the design variables, design constraints and optimization objectives in the multidisciplinary optimization text model.
[0075] Preferably, in the above-mentioned integrated method for supporting complex system design and optimization, the best optimization solution is obtained based on an intelligent optimization algorithm such as a multi-objective genetic algorithm NSGA2.
[0076] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses an integrated method that supports complex system design and optimization. In the problem domain, a preset graphic and text modeling framework is used to sequentially complete system requirement analysis, function analysis, and logical architecture model establishment. Subsequently, in the verification domain, an interpreter and a simulator are used to automatically generate a logical simulation model oriented to functional requirements to achieve functional requirement verification and provide guidance for the physical architecture model. In the solution domain, a physical architecture model is established through a preset graphic and text modeling framework. Subsequently, in the verification domain, an interpreter and a simulator are used to automatically generate an integrated simulation model oriented to functional requirements and non-functional requirements. In the optimization domain, a multidisciplinary optimization model is established through a preset graphic and text modeling framework and binding is established with the output values of the subsystem parameters and objective function-related variables in the physical architecture model in the solution domain. Ultimately, the best optimization solution obtained through iterative solution of the intelligent optimization algorithm is automatically fed back to the system design model through the optimization domain, realizing automatic verification of top-level requirements. Through a unified model characterization method, the system design, simulation and optimization of complex system models are integrated, breaking down the barriers between models at different stages, improving the efficiency of the complex system R&D process, and avoiding the problem of seamless integration of system optimization with system design and even simulation. BRIEF DESCRIPTION OF THE DRAWINGS
[0077] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in 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 embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.
[0078] Figure 1 A schematic diagram of an integrated method for supporting complex system design and optimization provided for the invention;
[0079] Figure 2The schematic diagram of the corresponding text and graphic of the demand model provided for the invention; wherein a is a schematic diagram of the demand graphic modeling model; b is a schematic diagram of the demand text modeling model;
[0080] Figure 3 A schematic diagram of the use case model provided by the invention corresponding to the graphic and text; wherein a is a schematic diagram of the use case graphic modeling model; b is a schematic diagram of the use case text modeling model;
[0081] Figure 4 The schematic diagram of the activity model provided by the invention corresponds to the graphic and text; wherein a is a schematic diagram of the activity graphic modeling model; b is a schematic diagram of the activity text modeling model;
[0082] Figure 5 A schematic diagram of the corresponding text and graphics of the coupling model provided by the invention; wherein a is a schematic diagram of the coupling graphic modeling model (definition diagram); b is a schematic diagram of the coupling graphic modeling model (connection diagram); c is a schematic diagram of the coupling text modeling model;
[0083] Figure 6 A schematic diagram of the correspondence between the discrete class model graphics and text provided by the invention; wherein a is a schematic diagram of the discrete class graphic modeling model (definition diagram); b is a schematic diagram of the discrete class graphic modeling model (state machine diagram); c is a schematic diagram of the discrete class text modeling model;
[0084] Figure 7 A schematic diagram of the correspondence between the graphics and text of the continuous class model provided by the invention; wherein a is a schematic diagram of the continuous class graphic modeling model (definition diagram); b is a schematic diagram of the continuous class graphic modeling model (equation diagram); c is a schematic diagram of the continuous class text modeling model;
[0085] Figure 8 A schematic diagram of the correspondence between the graphics and text of the multidisciplinary optimization model provided for the invention; wherein, a is a schematic diagram of the multidisciplinary optimization graphic modeling model; and b is a schematic diagram of the multidisciplinary optimization text modeling model. DETAILED DESCRIPTION
[0086] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0087] The embodiment of the present invention discloses an integrated method for supporting complex system design and optimization, such as Figure 1As shown in the figure, a unified model characterization method is used to integrate the system design, simulation and optimization of complex system models, breaking down the barriers between models at different stages, improving the efficiency of the complex system R&D process, and avoiding the problem of seamless integration of system optimization with system design and even simulation.
[0088] The specific steps of the integrated approach are as follows:
[0089] (1) Selecting a first graphic model framework and a first text model framework that are consistent with a preset metamodel in the problem domain to sequentially complete system requirement analysis, function analysis, and logical architecture model establishment;
[0090] The logical architecture model includes:
[0091] Requirement model framework, use case model framework, activity model framework, coupling model framework, discrete model framework, among which:
[0092] The requirement model framework is used to describe the stakeholders’ needs, system design requirements, and their requirement relationships;
[0093] The use case model framework is used to describe the functional scenarios of complex systems;
[0094] The activity model framework is used to describe the functional activity sequence that realizes the functional scenario of complex systems;
[0095] The coupled model framework is used to describe models in complex systems that are composed of atomic models or other coupled model components;
[0096] The discrete model framework is used to describe indivisible models with discrete behaviors in complex systems;
[0097] In order to further optimize the above technical solution, the first graphic model framework includes:
[0098] Requirements graphical modeling framework, use case graphical modeling framework, activity graphical modeling framework, coupling class graphical modeling framework, discrete class graphical modeling framework, among which:
[0099] The demand graph modeling framework consists of preset demand graphs;
[0100] The use case graphical modeling framework consists of preset use case diagrams;
[0101] The activity graph modeling framework consists of preset activity graphs;
[0102] The coupled graphical modeling framework is composed of a combination of preset definition graphs and connection graphs;
[0103] The discrete class graphical modeling framework consists of a combination of preset definition diagrams and state machine diagrams;
[0104] Specifically, the requirement diagram is used to describe stakeholders, stakeholder needs, system design requirements and the relationship between them; the use case diagram is used to describe the system, the use cases of the system, the participants and the relationship between them; the activity diagram is used to describe the functional activity interaction between the system and external units or the subsystems within the system; the definition diagram is used to describe the component parameters, state variables and input and output port types of the system graphical model framework; the connection diagram is used to describe the connection relationship between the components of the coupled class graphical model; the state machine diagram is used to describe the behavioral constraint relationship represented by the transition constraints between different states of the discrete class graphical model;
[0105] In order to further optimize the above technical solution, the first text model framework includes:
[0106] Requirement text modeling framework, use case text modeling framework, activity text modeling framework, coupling text modeling framework, discrete text modeling framework, among which:
[0107] The requirement text modeling framework consists of preset requirement texts;
[0108] The use case text modeling framework consists of preset use case texts;
[0109] The active text modeling framework consists of preset active text domains;
[0110] The coupled text modeling framework is composed of a combination of preset definition text and connection text;
[0111] The discrete class text modeling framework is composed of a combination of preset definition text and state machine text;
[0112] Specifically, the requirement text is used to describe stakeholders, stakeholder needs, system design requirements and the relationship between them; the use case text is used to describe the system, the use cases of the system, participants and the relationship between them; the definition text is used to describe the component parameters, state variables and input and output port types of the system text model; the connection text is used to describe the connection relationship between the components of the coupling text model; the state machine text is used to describe the behavior constraint relationship represented by the transition constraints between different states of the discrete text model;
[0113] (2) In the verification domain, the preset XLab interpreter and simulator are used to automatically generate a logical simulation model oriented to functional requirements to implement functional requirement verification and provide guidance for the physical architecture model;
[0114] Among them, the XLab interpreter and simulator are:
[0115] The XLab interpreter is used to generate cpp files from the system's logical architecture model;
[0116] The XLab simulator is used to combine all generated cpp files into a cpp engineering simulation project that conforms to the DEVS architecture.
[0117] (3) Selecting a preset metamodel consistent second graphic model framework and a second text model framework in the solution domain to establish a physical architecture model of the system;
[0118] The physical architecture model includes:
[0119] Coupling model framework, continuous model framework, discrete model framework, among which:
[0120] The coupled model framework is used to describe models in complex systems that are composed of atomic models or other coupled model components;
[0121] The continuous model framework is used to describe indivisible models with continuous behaviors in complex systems;
[0122] The discrete model framework is used to describe indivisible models with discrete behaviors in complex systems;
[0123] In order to further optimize the above technical solution, the second graphic model framework includes:
[0124] Coupled graphics modeling framework, continuous graphics modeling framework, discrete graphics modeling framework, among which:
[0125] The coupled graphical modeling framework is composed of a combination of preset definition graphs and connection graphs;
[0126] The continuous class graphical modeling framework is composed of a combination of preset definition graphs and equation graphs;
[0127] The discrete class graphical modeling framework consists of a combination of preset definition diagrams and state machine diagrams;
[0128] Specifically, the definition diagram is used to describe the component parameters, state variables, and input and output port types of the system graphical model framework; the connection diagram is used to describe the connection relationship between components of the coupled graphical model; the state machine diagram is used to describe the behavioral constraint relationship represented by the transition constraints between different states of the discrete graphical model;
[0129] In order to further optimize the above technical solution, the second text model framework includes:
[0130] Coupled text modeling framework, continuous text modeling framework, discrete text modeling framework, among which:
[0131] The coupled text modeling framework is composed of a combination of preset definition text and connection text;
[0132] The continuous text modeling framework is composed of a combination of preset definition text and equation text;
[0133] The discrete class text modeling framework is composed of a combination of preset definition text and state machine text;
[0134] Specifically, definition text is used to describe the component parameters, state variables and input and output port types of various models; connection text is used to describe the connection relationship between the components of the coupling model; equation text is used to describe the behavior constraint relationship represented by the ordinary differential / algebraic differential equation group in the continuous text model; state machine text is used to describe the behavior constraint relationship represented by the transition constraints between different states of the discrete text model;
[0135] (4) Automatically generate an integrated simulation model for functional and non-functional requirements in the verification domain through the preset XLab interpreter and simulator;
[0136] Among them, the XLab interpreter and simulator are:
[0137] The XLab interpreter is used to generate cpp files from the system's logical architecture model;
[0138] The XLab simulator is used to combine all generated cpp files into a cpp engineering simulation project that conforms to the DEVS architecture.
[0139] (5) In the optimization domain, the third graphical model framework and the third text model framework consistent with the preset metamodel are selected to establish a multidisciplinary optimization model and establish binding with the preset subsystem parameters and output values of the objective function-related variables in the physical architecture model in the solution domain. Finally, the best optimization solution obtained by iterative solution based on the intelligent optimization algorithm is automatically fed back to the system design model through the optimization domain to realize automatic verification of the top-level requirements.
[0140] Among them, the multidisciplinary optimization model framework is used to describe the multidisciplinary optimization object model of complex systems;
[0141] In order to further optimize the above technical solution, the third graphic model framework includes:
[0142] A multidisciplinary optimization graphical model framework, where:
[0143] The multidisciplinary optimization graphical model framework consists of preset definition graphs.
[0144] Further, the following are the general steps to obtain the best optimization solution based on intelligent optimization algorithms such as the multi-objective genetic algorithm NSGA-II:
[0145] 1. Problem definition: Determine the objective function of the optimization problem: Identify multiple objective functions that need to be optimized simultaneously, such as minimizing cost, maximizing performance, etc. Define decision variables: Identify the decision variables in the problem, that is, the parameters that can be adjusted. Determine constraints: If there are constraints, specify these conditions to limit the range of feasible solutions.
[0146] 2. Algorithm initialization:
[0147] Population initialization:
[0148] The initial population is randomly generated, and each individual in the population represents the value of a set of decision variables.
[0149] The individual encoding method can be selected according to the characteristics of the problem, such as binary encoding, real number encoding, etc.
[0150] 3. Non-dominated sorting:
[0151] Calculate the objective function value for each individual.
[0152] Perform a non-dominated sort on the population:
[0153] First, find all non-dominated individuals (i.e., no other individual is better than it in all objectives) and assign them to the first front (non-dominated front).
[0154] Then, continue to look for non-dominated individuals from the remaining individuals and assign them to the second frontier, and so on.
[0155] 4. Crowding calculation:
[0156] For each individual in the non-dominated front, calculate its crowding degree.
[0157] The crowding degree reflects the density of solutions around an individual and can be obtained by calculating the difference between adjacent individuals on each objective function.
[0158] Individuals with greater crowding degrees indicate that the solutions around them are sparser and have a greater chance of being retained during the selection process.
[0159] 5. Selection, crossover and mutation:
[0160] Select an action:
[0161] According to the non-dominated sorting and crowding degree, appropriate individuals are selected to form the parent population.
[0162] Common selection methods include tournament selection, roulette selection, etc.
[0163] Crossover operation:
[0164] Perform a crossover operation on the parent individuals to generate offspring individuals.
[0165] The crossover method can be selected according to the characteristics of the problem, such as single-point crossover, multi-point crossover, etc.
[0166] Mutation operation:
[0167] Perform mutation operations on offspring individuals to increase the diversity of the population.
[0168] The mutation method can be to randomly perturb some decision variables of the individual.
[0169] 6. Iterative Optimization:
[0170] Merge the offspring individuals with the parent individuals to form a new population.
[0171] Repeat the steps of non-dominated sorting, crowding calculation, selection, crossover and mutation until the termination condition is met.
[0172] The termination condition can be reaching the maximum number of iterations, convergence of the objective function value, etc.
[0173] 7. Results Analysis:
[0174] The final non-dominated frontier is a set of Pareto optimal solutions.
[0175] According to the needs of specific problems, the most suitable solution can be selected from the Pareto optimal solution as the best optimization solution.
[0176] For example, the selection can be made based on the decision maker's preferences, the requirements of the actual application, etc.
[0177] When implementing the NSGA-II algorithm, you can use programming languages such as C++ to implement each step. At the same time, you need to make appropriate adjustments and optimizations based on the specific optimization problem, such as adjusting algorithm parameters, selecting appropriate encoding methods and genetic operations, etc., to improve the performance and solution effect of the algorithm.
[0178] Specifically, the definition graph is used to describe the design variables, design constraints, and optimization objectives in the multidisciplinary optimization graphical model;
[0179] In order to further optimize the above technical solution, the third text model framework includes:
[0180] A framework of text models for multidisciplinary optimization, where:
[0181] The multidisciplinary optimization text model framework consists of preset definition texts.
[0182] Specifically, the definition text is used to describe the design variables, design constraints, and optimization objectives in the multidisciplinary optimization text model;
[0183] The following is further described in conjunction with specific embodiments:
[0184] First, in the problem domain, modelers perform graphical modeling on specific complex system objects based on the graphical modeling framework, where the graphical modeling framework includes 2 categories and 6 types of diagrams. The 2 categories include coupling and discrete types, and the 6 types of diagrams include requirement diagrams, use case diagrams, activity diagrams, definition diagrams, connection diagrams, and state machine diagrams.
[0185] Modelers select one or more corresponding types of diagrams from the above two categories and six types in accordance with the design theory of demand-function-logic-physical to automatically generate corresponding text models. In the preset graphic modeling framework, they can select from the demand diagram graphic modeling framework, use case diagram graphic modeling framework, activity diagram graphic modeling framework, coupling class graphic modeling framework, and discrete class graphic modeling framework, specifically:
[0186] Requirements Graph Graphical modeling framework, including: Requirement graph, used to describe stakeholders, stakeholder needs, system design requirements and the requirement relationships between them;
[0187] Use Case Diagrams Graphical modeling framework, including: Use Case Diagrams, which are used to describe the system, its use cases, actors, and the relationships between them;
[0188] Activity diagram graphical modeling framework, including: Activity diagram, used to describe the functional activity interaction between the system and external units or subsystems within the system;
[0189] A coupling-type graphical modeling framework, including: a definition diagram and a connection diagram, which are used to describe coupling models in complex systems, wherein the definition diagram defines the hierarchical structure of the coupling model, and the connection diagram defines the connection relationship between its components;
[0190] The discrete class graphical modeling framework includes: definition diagram and state machine diagram, which are used to describe the indivisible model with discrete behavior in complex systems. The definition diagram defines the relevant parameters, state variables, input and output ports of the discrete class model, and the state machine diagram defines the discrete behavior constraints of the discrete class model with the definition of state and conversion logic.
[0191] According to the preset text modeling framework, the corresponding textual models are automatically generated from the two categories and six types of diagrams. The requirement diagram is textualized to obtain the textual model of the requirement diagram, the use case diagram is textualized to obtain the textual model of the use case diagram, the activity diagram is textualized to obtain the textual model of the activity diagram, the definition diagram and the connection diagram are textualized to obtain the textual model of the coupling class, and the definition diagram and the state machine diagram are textualized to obtain the textual model of the discrete class.
[0192] The preset text modeling framework includes: requirement text, use case text, activity text, definition text, connection text and state machine text, wherein the requirement text is used to describe stakeholders, stakeholder needs, system design requirements and the relationship between them; the use case text is used to describe the system, the system's use cases, participants and the relationship between them; the activity text is used to describe the functional activity interaction between the system and external units or the subsystems within the system; the definition text is used to describe the component parameters, state variables and input and output port types of the several models; the connection text is used to describe the connection relationship between the components of the coupling model; the state machine area is used to describe the behavioral constraint relationship of the discrete class model represented by different states and the transition constraints between them.
[0193] A textualized model is obtained according to a preset text modeling framework, and the requirement diagram, use case diagram, activity diagram, definition diagram, connection diagram and state machine diagram are respectively matched with the requirement text, use case text, activity text, definition text, connection text and state machine text; a textualized model is automatically generated according to the content of the requirement text, use case text, activity text, definition text, connection text and state machine text;
[0194] The textualized models of the coupled classes and discrete classes are interpreted into C++ codes by an interpreter to run logic simulation under the DEVS simulator.
[0195] In the verification domain, the logical simulation model generated by the problem domain is simulated and verified against the functional requirements.
[0196] In the solution domain, modelers will guide the development of the physical architecture based on the logical architecture in the problem domain. Modelers perform graphical modeling on specific complex system objects based on the graphical modeling framework, where the graphical modeling framework includes 3 categories and 4 types of diagrams. The 3 categories include coupling, continuous, and discrete, and the 4 types of diagrams include definition diagrams, connection diagrams, equation diagrams, and state machine diagrams.
[0197] Modelers select one or more corresponding graphs from the above three categories and four types of graphs in accordance with the design theory of demand-function-logic-physics to automatically generate corresponding text models. In the preset graphic modeling framework, they can select from the coupled graphic modeling framework, the continuous graphic modeling framework, and the discrete graphic modeling framework, specifically:
[0198] A coupling-type graphical modeling framework, including: a definition diagram and a connection diagram, which are used to describe coupling models in complex systems, wherein the definition diagram defines the hierarchical structure of the coupling model, and the connection diagram defines the connection relationship between its components;
[0199] The continuous graphical modeling framework includes: definition graph and equation graph, which are used to describe the indivisible model with continuous behavior in complex systems. The definition graph defines the relevant parameters, state variables, input and output ports of the continuous model, and the equation graph defines the continuous behavior constraints of the continuous model with ordinary differential / algebraic differential equations.
[0200] The discrete class graphical modeling framework includes: definition diagram and state machine diagram, which are used to describe the indivisible model with discrete behavior in complex systems. The definition diagram defines the relevant parameters, state variables, input and output ports of the discrete class model, and the state machine diagram defines the discrete behavior constraints of the discrete class model with the definition of state and conversion logic.
[0201] According to the preset text modeling framework, the corresponding textual models are automatically generated for the three categories and four types of diagrams. The definition diagram and the connection diagram are textualized to obtain the textual model of the coupling class, the definition diagram and the equation diagram are textualized to obtain the textual model of the continuous class, and the definition diagram and the state machine diagram are textualized to obtain the textual model of the discrete class.
[0202] The preset text modeling framework includes: definition text, connection text, equation text and state machine text, wherein the definition text is used to describe the component parameters, state variables and input and output port types of the several models; the connection text is used to describe the connection relationship between the components of the coupling model; the equation text is used to describe the behavioral constraint relationship of the continuous type model represented by the ordinary differential / algebraic differential equation group; the state machine text is used to describe the behavioral constraint relationship of the discrete type model represented by different states and the conversion constraints between them.
[0203] A textualized model is obtained according to a preset text modeling framework, and a definition diagram, a connection diagram, an equation diagram, and a state machine diagram are respectively matched with a definition text, a connection text, an equation text, and a state machine text; a textualized model is automatically generated according to the contents of the definition text, the connection text, the equation text, and the state machine text;
[0204] The textualized models of the coupled class, continuous class and discrete class will be interpreted into C++ codes by the interpreter to run the full system simulation under the DEVS simulator.
[0205] In the verification domain, the physical simulation model generated by the solution domain performs co-simulation verification for functional and non-functional requirements and outputs variable values related to the optimization objective function.
[0206] In the optimization domain, the modeler will define the system multidisciplinary optimization model based on the physical architecture in the solution domain. The modeler performs graphical modeling on the multidisciplinary optimization object based on the graphical modeling framework, where the graphical modeling framework includes a definition diagram;
[0207] Modelers will automatically generate corresponding text models for the definition diagram. In the preset graphic modeling framework, there is a multidisciplinary optimization graphic modeling framework, which is as follows:
[0208] Optimization graphical modeling framework, including: definition diagrams, used to describe design variables, design constraints and optimization objectives in multidisciplinary optimization graphical models;
[0209] According to the preset text modeling framework, the definition graph is textualized to obtain a textual model of the multidisciplinary optimization class.
[0210] The preset text modeling framework includes: definition text, wherein the definition text is used to describe system design variables, design constraints and optimization goals.
[0211] A textualized model is obtained according to a preset text modeling framework, and the definition diagram is matched with the definition text respectively; a textualized model is automatically generated according to the content of the definition text;
[0212] The design variables of the optimization class are bound to the parameters of the subsystem through the connection diagram of the coupling class.
[0213] The textual model of multidisciplinary optimization will be sent to the customized intelligent optimization algorithm for iterative solution to obtain the best optimization solution, which will be automatically fed back to the system design model through the binding of the optimization domain and can automatically verify the top-level requirements.
[0214] like Figures 2 to 8 As shown, the requirement graph in the requirement graph graphical modeling framework corresponds to the requirement text in the requirement graph text modeling framework, which is used to define stakeholders, stakeholder needs, system design requirements and the requirement relationships between them;
[0215] The use case diagram in the graphical modeling framework corresponds to the use case text in the use case diagram textual modeling framework and is used to define the system, its use cases, actors, and the relationships between them;
[0216] The use case diagram in the activity diagram graphical modeling framework corresponds to the activity text in the activity diagram text modeling framework, which is used to define the functional activity interaction between the system and external units or the subsystems within the system;
[0217] The definition diagram in the coupled class model graphical modeling framework corresponds to the definition text in the coupled class model text modeling framework, and is used to define the hierarchical structure information of the coupled class model, including structural characteristics such as components, references, and ports; the connection diagram in the coupled class model graphical modeling framework corresponds to the connection text in the coupled class model text modeling framework, and is used to define the connection relationship between the components of the coupled class model;
[0218] The definition diagram in the discrete class model graphical modeling framework corresponds to the definition text in the discrete class model text modeling framework, which is used to define the structural information of the discrete class model, including instantiation parameters, state variables, references, ports and other structural characteristics; the state machine diagram in the discrete class model graphical modeling framework corresponds to the state machine text in the discrete class model text modeling framework, which is used to define the discrete behavior constraint relationship of the discrete class model based on event-triggered state transition;
[0219] The definition diagram in the continuous class model graphical modeling framework corresponds to the definition area in the continuous class model text modeling framework, which is used to define the structural information of the continuous class model, including instantiation parameters, state variables, references, ports and other structural characteristics; the equation diagram in the continuous class model graphical modeling framework corresponds to the equation text in the continuous class model text modeling framework, which defines the continuous behavior constraint relationship of the continuous class model based on continuous time changes with ordinary differential / algebraic differential equations;
[0220] The definition diagram in the graphical modeling framework of the multidisciplinary optimization class model corresponds to the definition text in the text modeling framework of the multidisciplinary optimization class model, which is used to define system design variables, design constraints and optimization objectives.
[0221] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.
[0222] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. An integrated approach to support complex system design and optimization, characterized in that: include: Divide the model hierarchy into problem domain, solution domain, verification domain and optimization domain according to modeling requirements; Selecting a preset first graphic model framework and a first text model framework that are consistent with the metamodel in the problem domain to sequentially complete the system's requirement analysis, function analysis, and logical architecture model establishment; In the verification domain, the preset XLab interpreter and simulator automatically generate a logical simulation model oriented to functional requirements to implement functional requirement verification and provide guidance for the physical architecture model; Selecting a preset second graphic model framework and a second text model framework that are consistent with the metamodel in the solution domain to establish a physical architecture model of the system; In the verification domain, the integrated simulation model for functional and non-functional requirements is automatically generated through the preset XLab interpreter and simulator; A third graphical model framework and a third text model framework that are preset and consistent with the metamodel are selected in the optimization domain to establish a multidisciplinary optimization model, wherein the multidisciplinary optimization model is used to describe a multidisciplinary optimization object model of a complex system; and a binding is established with the output values of the subsystem parameters and the objective function-related variables preset in the physical architecture model in the solution domain; The best optimization solution obtained based on the intelligent optimization algorithm is automatically fed back to the system design model through the optimization domain to achieve automatic verification of top-level requirements.
2. An integrated method for supporting complex system design and optimization according to claim 1, characterized in that: The logical architecture model includes: Requirement model framework, use case model framework, activity model framework, coupling model framework, discrete model framework, among which: The requirement model framework is used to describe the needs of stakeholders, system design requirements, and the relationship between the two requirements; The use case model framework is used to describe the functional scenarios of complex systems; The activity model framework is used to describe the functional activity sequence that realizes the functional scenario of complex systems; The coupled model framework is used to describe models in complex systems that are composed of atomic models or other coupled model components; The discrete class model framework is used to describe indivisible models with discrete behaviors in complex systems.
3. The integrated method for supporting complex system design and optimization according to claim 1, characterized in that: The graphical model framework includes: Requirements graphical modeling framework, use case graphical modeling framework, activity graphical modeling framework, coupling class graphical modeling framework, discrete class graphical modeling framework, among which: The demand graph modeling framework consists of preset demand graphs; The use case graphical modeling framework consists of preset use case diagrams; The activity graph modeling framework consists of preset activity graphs; The coupled graphical modeling framework is composed of a combination of preset definition graphs and connection graphs; The discrete class graphical modeling framework consists of a combination of preset definition diagrams and state machine diagrams; The requirement diagram is used to describe stakeholders, stakeholder needs, system design requirements, and the relationship between the requirements; The use case diagram is used to describe the system, the use cases of the system, the participants and the relationship between the three; The activity diagram is used to describe the functional activity interaction between the system and external units or the subsystems within the system; The definition diagram is used to describe the component parameters, state variables and input and output port types of the system graphical model framework; The connection diagram is used to describe the connection relationship between the components of the coupling class graphic model; The state machine diagram is used to describe the behavior constraint relationship represented by the transition constraints between different states of the discrete class graphic model.
4. The integrated method for supporting complex system design and optimization according to claim 1, characterized in that: The text model framework includes: Requirement text modeling framework, use case text modeling framework, activity text modeling framework, coupling text modeling framework, discrete text modeling framework, among which: The requirement text modeling framework consists of preset requirement texts; The use case text modeling framework consists of preset use case texts; The active text modeling framework consists of preset active text domains; The coupled text modeling framework is composed of a combination of preset definition text and connection text; The discrete class text modeling framework is composed of a combination of preset definition text and state machine text; The requirement text is used to describe stakeholders, stakeholder needs, system design requirements, and the relationship between the three requirements; The use case text is used to describe the system, the use cases of the system, the participants, and the relationship between the three; The definition text is used to describe the component parameters, state variables and input and output port types of the system text model; The connection text is used to describe the connection relationship between components of the coupling class text model; The state machine text is used to describe the behavior constraint relationship represented by the transition constraints between different states of the discrete class text model.
5. The integrated method for supporting complex system design and optimization according to claim 1, characterized in that: The physical architecture model framework includes: Coupling model framework, continuous model framework, discrete model framework, among which: The coupled model framework is used to describe models in complex systems that are composed of atomic models or other coupled model components; The continuous model framework is used to describe indivisible models with continuous behaviors in complex systems; The discrete class model framework is used to describe indivisible models with discrete behaviors in complex systems.
6. The integrated method for supporting complex system design and optimization according to claim 1, characterized in that: The second graphic model framework includes: Coupled graphics modeling framework, continuous graphics modeling framework, discrete graphics modeling framework, among which: The coupled graphical modeling framework is composed of a combination of preset definition graphs and connection graphs; The continuous class graphical modeling framework is composed of a combination of preset definition graphs and equation graphs; The discrete class graphical modeling framework consists of a combination of preset definition diagrams and state machine diagrams; The definition diagram is used to describe the component parameters, state variables and input and output port types of the system graphical model framework; The connection diagram is used to describe the connection relationship between components of the coupling type graphic model; The equation graph is used to describe the behavior constraint relationship represented by the ordinary differential / algebraic differential equation group in the continuous class graphical model; The state machine diagram is used to describe the behavior constraint relationship represented by the transition constraints between different states of the discrete class graphic model.
7. The integrated method for supporting complex system design and optimization according to claim 1, characterized in that: The second text model framework includes: The second text model framework includes: Coupled text modeling framework, continuous text modeling framework, discrete text modeling framework, among which: The coupled text modeling framework is composed of a combination of preset definition text and connection text; The continuous text modeling framework is composed of a combination of preset definition text and equation text; The discrete class text modeling framework is composed of a combination of preset definition text and state machine text; The definition text is used to describe the component parameters, state variables and input and output port types of various models; The connection text is used to describe the connection relationship between the components of the coupling model; The equation text is used to describe the behavior constraint relationship represented by the ordinary differential / algebraic differential equation system in the continuous text model; The state machine text is used to describe the behavior constraint relationship represented by the transition constraints between different states of the discrete class text model.
8. The integrated method for supporting complex system design and optimization according to claim 1, characterized in that: The third graphical model framework includes: a multidisciplinary optimization graphical model framework, wherein: The multidisciplinary optimization graphic model framework is composed of a preset definition diagram; the definition diagram is used to describe the design variables, design constraints and optimization objectives in the multidisciplinary optimization graphic model.
9. The integrated method for supporting complex system design and optimization according to claim 1, characterized in that: The third text model framework includes: a multidisciplinary optimization text model framework, wherein: the multidisciplinary optimization text model framework is composed of preset definition texts; the definition texts are used to describe the design variables, design constraints and optimization objectives in the multidisciplinary optimization text model.
10. The integrated method for supporting complex system design and optimization according to claim 1, characterized in that: The best optimization solution is obtained through intelligent optimization algorithms such as the multi-objective genetic algorithm NSGA2.