基于元模型的工程系统仿真建模方法及应用研究
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摘要
目前仿真技术和建模方法已经有了一定的研究,但针对工程系统,其仿真和建模方法的研究集中于对特定的工程系统的建模与仿真,缺乏对建模过程的理论基础和规范的建模过程方法论的研究。且由于工程系统的复杂程度,建模工作量大,模型维护和修改困难,进一步限制了仿真方法在工程系统中的应用。本文针对这种情况,提出基于三种元模型的工程系统进行建模方法及其理论基础。
作为工程模型,无论其复杂程度如何,都可以分解为三个部分,即逻辑部分,物理部分和控制决策部分。这三个部分具有不同的特点,具有一定的层次关系,且互相作用形成工程系统。本文提出的建模仿真框架基于工程系统的这种结构,采用三种元模型,即任务模型、实体模型和控制模型分别对工程系统的三个部分进行建模,反映系统的不同侧面。在不同的建模中,根据建模对象的特点,分别采用不同的策略进行建模。并且三种元模型互相作用,形成工程系统的完整仿真框架。任务元模型面向设计和建模初期的任务规划过程,是工程系统中逻辑部分在仿真模型中的映射。通过面向实际工程技术人员的分解技术,逐层对整个工程任务进行细化,每一层面向相应的实际工程管理设计人员,分解到最后一层,得到面向工程实施技术人员的基本任务集；然后利用有向图作为分析工具,建立每个层次的任务逻辑图,表征任务之间的逻辑依赖关系,并利用有向图的邻接矩阵和依赖矩阵对任务关系进行分析,寻找产生死锁的任务集,对基本任务集进行逻辑关系上的层次划分处理,得到整个任务系统的逻辑结构。它是进一步进行任务详细分析与设计建模的基础
实体元模型是整个仿真系统的基础,是工程系统中物理部分在仿真模型中的应用。物理部分在工程中表现出明显的混合特征,即同时具有离散系统和连续系统的特征,因此采用混合系统理论来分析和建模工程实体。本文提出采用两种模型：对象模型以及状态模型,前者用于描述模型的数据以及数据之间的关系,是系统的静态结构,而后者用于描述系统的状态以及状态之间的变迁,是系统的动态模型。本文推导了相应的数学描述形式,并在此基础上建立了混合系统的对象模型,建立了以混合自动机表达的状态模型。
控制元模型是实际工程系统控制决策部分在仿真系统中的映射。本文建立了控制单元模型及其形式表达。提出分三步对控制过程进行建模：将实际工程步表达为协作图；将实际工程步转换为序列图；引入控制单元,将实际工程步序列图转换为仿真系统序列图。并对控制元模型进行面向工程步和面向任务的模块化,以减少建模的复杂程度和工作量。控制元模型在仿真系统中属于承上启下的位置,通过建立控制模型,连接宏观的任务模型与微观的实体模型,可以得到工程系统完整的系统模型。
本文展示了一个大型激光工程装置的建模和仿真过程。验证了本文提出的建模和仿真方法。通过仿真的运行,在设计阶段进行结构方案的比对,在建造阶段进行建造方案的验证和优化,在运行阶段对运行状态进行仿真。在不同的阶段,均对实际激光工程装置的设计和建造起到了指导和优化的作用,节省了大量的时间和人力物力,取得了良好的效果。
While the research of modeling and simulation technology has been developed for decades, its application engineering system has been focused on specified engineering system. Few researches have been done on its theoretical basis and the meth of the modeling process. Because the complexity, the model of engineering system is hard to build, to maintain and to modify, thus its application is limited. An approach of modeling of engineering system which based on the mete-models and its theoretical basis is established in this thesis.
An engineering system is made up by three parts which are named the logic part, the physic part and the control and decision part. They have different characteristics, relate and react to each other hierarchy. Based on the construction of engineering system, three meta-models is built to model the different part respectively. They are task meta-model, object meta-model and control meta-model. In the modeling of three meta-models, different strategies are used respectively. The meta-models affect to each other and make up the simulation framework of the engineering system.
Task meta-models oriented to the task planning and design process of the system modeling. The engineer of the real system will decompose the engineering system hierarchy. Every level of the task model is oriented to its engineers of the real system. At the last level, the basic task model will obtained. The directed graph is hired to analyze the task model. The logic graph is built to describe the logic relationship of the tasks. The adjacency matrix and the rely matrix are hired to find the deadlock of the tasks. The task logic structure of the entire system is obtained by describe the logic level of the basic task models. It is the basis of the further task analyze and modeling process.
Entity meta-models are the basis of the entire simulation system. They are the map of the physic part of the engineering system. Physic parts have characteristics of hybrid system.the hybrid system theory is hired to analyze and model the physic part. Two kinds of models, named object model and status object, are hired to describe the physic part. The former describes the date of the model and the relation of the date. It is the static structure of the model. The latter describes the status of the system and their relation. It is the dynamic structure of the system. The mathematic description of the model is given and the object model based on hybrid system and the status model based on hybrid automaton are built.
Control meta-models are the map of the control and decision part of the engineering system. The structure of the control meta-model and its mathematic description are built. The modeling process of control model is also given. First, the real engineering step is described to collaboration graphs. Then the collaboration graphs are transmitted to sequence graphs. Last, the control model is introduced and the sequence graphs of real engineering system are transmitted to the sequence graphs of the simulation system. The control models are modularized according to the engineering steps and tasks to reduce the complexity and the workload of modeling. Control models link the task models and the entity models and the system model will obtained by the linkage.
The modeling and simulation approach is verified by the virtual construction of a large scale laser system which is modeling by the approach. The structure design is contrasted at the structure design stage and the construction plan is optimized at the construction stage through the simulation. At every stage, the simulation guide and optimize the real design and construction of the laser system. The time and cost of the engineering system are reduced and the modeling approach proved to be effective.
作为工程模型,无论其复杂程度如何,都可以分解为三个部分,即逻辑部分,物理部分和控制决策部分。这三个部分具有不同的特点,具有一定的层次关系,且互相作用形成工程系统。本文提出的建模仿真框架基于工程系统的这种结构,采用三种元模型,即任务模型、实体模型和控制模型分别对工程系统的三个部分进行建模,反映系统的不同侧面。在不同的建模中,根据建模对象的特点,分别采用不同的策略进行建模。并且三种元模型互相作用,形成工程系统的完整仿真框架。任务元模型面向设计和建模初期的任务规划过程,是工程系统中逻辑部分在仿真模型中的映射。通过面向实际工程技术人员的分解技术,逐层对整个工程任务进行细化,每一层面向相应的实际工程管理设计人员,分解到最后一层,得到面向工程实施技术人员的基本任务集；然后利用有向图作为分析工具,建立每个层次的任务逻辑图,表征任务之间的逻辑依赖关系,并利用有向图的邻接矩阵和依赖矩阵对任务关系进行分析,寻找产生死锁的任务集,对基本任务集进行逻辑关系上的层次划分处理,得到整个任务系统的逻辑结构。它是进一步进行任务详细分析与设计建模的基础
实体元模型是整个仿真系统的基础,是工程系统中物理部分在仿真模型中的应用。物理部分在工程中表现出明显的混合特征,即同时具有离散系统和连续系统的特征,因此采用混合系统理论来分析和建模工程实体。本文提出采用两种模型：对象模型以及状态模型,前者用于描述模型的数据以及数据之间的关系,是系统的静态结构,而后者用于描述系统的状态以及状态之间的变迁,是系统的动态模型。本文推导了相应的数学描述形式,并在此基础上建立了混合系统的对象模型,建立了以混合自动机表达的状态模型。
控制元模型是实际工程系统控制决策部分在仿真系统中的映射。本文建立了控制单元模型及其形式表达。提出分三步对控制过程进行建模：将实际工程步表达为协作图；将实际工程步转换为序列图；引入控制单元,将实际工程步序列图转换为仿真系统序列图。并对控制元模型进行面向工程步和面向任务的模块化,以减少建模的复杂程度和工作量。控制元模型在仿真系统中属于承上启下的位置,通过建立控制模型,连接宏观的任务模型与微观的实体模型,可以得到工程系统完整的系统模型。
本文展示了一个大型激光工程装置的建模和仿真过程。验证了本文提出的建模和仿真方法。通过仿真的运行,在设计阶段进行结构方案的比对,在建造阶段进行建造方案的验证和优化,在运行阶段对运行状态进行仿真。在不同的阶段,均对实际激光工程装置的设计和建造起到了指导和优化的作用,节省了大量的时间和人力物力,取得了良好的效果。
While the research of modeling and simulation technology has been developed for decades, its application engineering system has been focused on specified engineering system. Few researches have been done on its theoretical basis and the meth of the modeling process. Because the complexity, the model of engineering system is hard to build, to maintain and to modify, thus its application is limited. An approach of modeling of engineering system which based on the mete-models and its theoretical basis is established in this thesis.
An engineering system is made up by three parts which are named the logic part, the physic part and the control and decision part. They have different characteristics, relate and react to each other hierarchy. Based on the construction of engineering system, three meta-models is built to model the different part respectively. They are task meta-model, object meta-model and control meta-model. In the modeling of three meta-models, different strategies are used respectively. The meta-models affect to each other and make up the simulation framework of the engineering system.
Task meta-models oriented to the task planning and design process of the system modeling. The engineer of the real system will decompose the engineering system hierarchy. Every level of the task model is oriented to its engineers of the real system. At the last level, the basic task model will obtained. The directed graph is hired to analyze the task model. The logic graph is built to describe the logic relationship of the tasks. The adjacency matrix and the rely matrix are hired to find the deadlock of the tasks. The task logic structure of the entire system is obtained by describe the logic level of the basic task models. It is the basis of the further task analyze and modeling process.
Entity meta-models are the basis of the entire simulation system. They are the map of the physic part of the engineering system. Physic parts have characteristics of hybrid system.the hybrid system theory is hired to analyze and model the physic part. Two kinds of models, named object model and status object, are hired to describe the physic part. The former describes the date of the model and the relation of the date. It is the static structure of the model. The latter describes the status of the system and their relation. It is the dynamic structure of the system. The mathematic description of the model is given and the object model based on hybrid system and the status model based on hybrid automaton are built.
Control meta-models are the map of the control and decision part of the engineering system. The structure of the control meta-model and its mathematic description are built. The modeling process of control model is also given. First, the real engineering step is described to collaboration graphs. Then the collaboration graphs are transmitted to sequence graphs. Last, the control model is introduced and the sequence graphs of real engineering system are transmitted to the sequence graphs of the simulation system. The control models are modularized according to the engineering steps and tasks to reduce the complexity and the workload of modeling. Control models link the task models and the entity models and the system model will obtained by the linkage.
The modeling and simulation approach is verified by the virtual construction of a large scale laser system which is modeling by the approach. The structure design is contrasted at the structure design stage and the construction plan is optimized at the construction stage through the simulation. At every stage, the simulation guide and optimize the real design and construction of the laser system. The time and cost of the engineering system are reduced and the modeling approach proved to be effective.
引文
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