A high performance framework for modeling and simulation of large-scale complex systems

Due to the quick advances in the scale of problem domain of complex systems under investigation, the complexity of multi-input component models used to construct logical processes (LP) has significantly increased. High-performance computing technologies have therefore been extensively used to enable parallel simulation execution. However, the traditional multi-process parallel method (MPM) executes LPs in parallel on multi-core platforms, which ignores the intrinsic parallel capabilities of multi-input component models. In this study, a vectorized component model (VCM) framework has been proposed. The design aims to better utilize the parallelism of multi-input component models. A two-level composite parallel method (CPM) has then been constructed within the framework, which can sustain complex system simulation applications consisting of multi-input component models. CPM first employs MPM to dispatch LPs onto a multi-core computing platform. It then maps VCMs to the multiple-core platform for parallel execution. Experimental results indicate that (1) the proposed VCM framework can better utilize the parallelism of multi-input component models, and (2) CPM can significantly improve the performance comparing to the traditional MPM. The results also show that CPM can effectively cope with the size and complexity of complex simulation applications with multi-input component models.     

Modelling and simulation of complex manufacturing systems using statechart-based actors

This paper describes a multi-agent architecture based on the actors computational model, for the distributed simulation of discrete event systems whose entities have a complex dynamic behaviour. Complexity is dealt with by exploiting statechart-based actors which constitute the basic building blocks of a model. Actors are lightweight reactive autonomous agents that communicate to one another by asynchronous message passing. The thread-less character of actors saves memory space and fosters efficient execution. The behaviour of actors is specified through “distilled statecharts” that enable hierarchical and modular specifications. Distributed simulation is achieved by partitioning a system model among a set of logical processes (theatres). Timing management and inter-theatre communications rest in a case on the High Level Architecture services. The paper illustrates the practical application of the proposed modelling and simulation methodology by specifying and analysing a complex manufacturing system.     

基于模糊神经网络的Agent反应器结构及实现

针对复杂适应系统(ComplexAdaptiveSystem,CAS)仿真中的Agent结构建模问题,提出了一种基于模糊神经网络的Agent反应器结构及实现,以提高Agent混合模型的性能,满足复杂适应系统仿真中对Agent反应器的快速性、自适应性与准确性的要求。最后,结合跨流域调水管理复杂适应系统仿真中Agent反应器的规则存储与推理过程,进行了实例分析。     

一类通用的适应性软件体系结构风格研究

研究并提出一类通用的适应性软件体系结构风格.通过对适应性软件体系结构的基本特性分析,抽取适应性软件体系结构的通用框架,建立基于多视图建模理论的集成化适应性软件体系结构参考模型,给出多视图模型的演化与映射规律.基于元建模和图转换理论,提出模型映射一致性算法.最后,建立了适应性软件体系结构支撑环境.适应性软件体系结构适用于复杂软件系统,特别是网络环境下大型、开放式软件系统的开发和实施.     

Knowledge-based environment for investigating multicomputer architectures

Multicomputers for massively parallel processing will eventually employ billions of processing elements, each of which will be capable of communicating with every other processing element. A knowledge-based modelling and simulation environment (KBMSE) for investigating such multicomputer architecture at a discrete-event system level is described. The KBMSE implements the discrete-event system specification (DEVS) formalism in an object-oriented programming system of Scheme (a dialect), which supports building models in a hierarchical, modular manner, a systems-oriented approach not possible in conventional simulation languages. The paper presents a framework for knowledge-based modelling and simulation by exemplifying modelling a hypercube multicomputer architecture in the KBMSE. The KBMSE has been tested on a variety of domains characterized by complex, hierarchical structures such as advanced multicomputer architectures, local area computer networks, intelligent multi-robot organizations, and biologically based life-support systems.     

基于人工生命方法的作战仿真模型研究

简要介绍了人工生命的概念、基本原理与方法，指出它是解决复杂系统的有效途径。作战是典型的复杂自适应系统(CAS)，传统的作战仿真方法(如兰彻斯特方程)将作战视为确定性过程，难以将许多重要的无形因素进行建模。将人工生命方法应用于作战仿真，以细胞自动机为工具，通过多智能体的相互作用来研究系统高层的突现行为，可以更好地揭示作战的本质和作战过程的演化规律。讨论了基于人工生命方法的作战仿真的一般过程和智能体的结构模型，总结了作战仿真新方法的特点，最后展望了今后的研究工作。     

Sensory interactive robot trajectory control using a real-time world model

A major consideration in the design of sensory interactive trajectory generation software for a Flight Telerobotic Servicer (FTS) is the availability and maintenance of a current model of the manipulator's world. The NASA/NBS Standard Reference Model for Telerobot Control System Architecture (NASREM), which has been adopted by NASA for control of the FTS, provides a logical computing architecture for telerobotics. It defines a hierarchical control system in which complex tasks are decomposed into progressively simpler subtasks, or objectives. It contains a hierarchy of world modeling modules which maintain the system's internal model of the manipulator and its world by continuously updating the model based upon sensory data. Each world modeling module contains support processes or functions which simultaneously and asynchronously support sensory processing and task decomposition. This paper discusses the role of world modeling in support of trajectory generation and execution. For sensory interactive robot motion control, the world modeling modules must operate rapidly so that the model of the world remains in registration with the real world.This paper discusses the world modeling modules of a hierarchical control system which facilitate sensory interactive trajectories by decoupling and supporting the sensory and manipulator planning processes. We define the types of information which should be included in the interfaces to the modules, as well as the modules' structure and function. Finally, we discuss the real-time implementation and experimental results of a particular sensory interactive algorithm performed in our laboratory.     

SYSTEM THEORETIC FORMALISMS FOR COMBINED DISCRETE-CONTINUOUS SYSTEM SIMULATION

In this paper we present an approach to combined discrete-continuous modelling which can be used to model and simulate an intelligent multi-layer control architecture as can be found in high autonomy systems. The modelling approach is based on system theoretical concepts; the three system specification formalisms-differential equation, discrete time, and the discrete event system specification formalism-have been combined to facilitate multi-formalisms modelling. Simulation concepts are based on the abstract simulator concept for discrete event simulation developed by Zeigler. Similar simulation methods have been developed to simulate modular, hierarchical discrete time and differential equation specified systems as well as multi-formalism models. Included in the paper are several examples of multi-formalism models together with the simulation results from the STIMS environment-an implementation of the modelling and simulation concepts in Interlisp-D/LOOPS.     

离散信号事件驱动的自动测试系统仿真验证方法与实现

为在设计早期对复杂自动测试系统进行充分验证从而加速其成熟并降低研发成本,对离散事件系统规范进行扩展和改进,在原子模型中引入了端口和故障模式,通过端口间的连接构成耦合模型,提出一种离散信号事件驱动的仿真调度算法,并给出一个C/S架构的支持远程交互的仿真验证实现方案;基于自研的SCATS自动测试系统软件平台,分别针对一个示例系统和真实系统开展了实验,结果表明所提模型和方法支持复杂系统多分辨率层次化建模,仿真具有较高的一致性和执行效率,满足自动测试系统仿真验证工程应用需求。     

EXPERIMENTAL FRAME SPECIFICATION METHODOLOGY FOR HIERARCHICAL SIMULATION MODELING

A methodology is presented for defining conditions under which simulation models can be observed and experimented with. Such conditions are formalized as experimental frames. A method for deriving experimental frame specifications for simulation models is given based on a universal specification called generic experimental frame. The methodology defines two schemes for carrying out simulation experiments with hierarchical, modular models: 1 the centralized architecture is based on a global experimental frame which specifies conditions for the entire model; 2 the distributed architecture facilitates attachments of frame components to model simulators at different levels of the model hierarchy. An example of a simple manufacturing process illustrates the conceptual framework. Implications of the proposed framework for design of high autonomy systems are discussed as well.     

A conceptual design aid environment for expert-database systems

With the actual penetration of expert systems into the business world, the question is, how the expert system idea can be used to enhance the existing information systems with more intelligence in usage and operation. This interest is not surprising due to the advancement of the fifth generation of computer technology, and avid interest in the field of Artificial Intelligence. Therefore design of an information system for an application becomes more complex, and the inability of the human designer to deal with it increases. For designing intelligent systems, we have to be able to forecast the behavior of the information system more precisely before implementing it, i.e. we'have to support the specification process.Clearly the technology, such as Data base systems, is leading on efficiency issues as those needed for the construction, retrieval and manipulation of large shared data base. On the other hand, the AI techniques have improved significantly with function such as deductive reasoning and natural language processing. It is important to find way to merge these technologies into one mainstream of computing. A meeting point for the two areas is the issue of conceptual knowledge modelling, so that models can be created that will define the role and the ways to use data in AI systems. In the framework of this study, one possible expert system design aid environment has been suggested to assist the designer in his work.In a conceptual modelling environment a model is given for analysing complex real world problems known as the Conceptual Knowledge Model (CKM), represented by a Graphical and a Formal Representation. The Graphical Representation consists of three graphs: Conceptual Requirement Graph, Conceptual Behavior Graph, and Conceptual Structure Graph. These graphs are developed by involving the expert during the design process. The graphs are then transformed into first-order predicate logic to represent the logical axioms of a theory, which constitutes the knowledge base of the Expert System. The model suggested here is a step towards closing the gap between the theory of the conventional data base theory and AI databases.     

基于复杂适应系统的复合多层次遗传算法

针对研究复杂适应系统(CAS),建立系统模型中所遇到的困难和问题,根据复杂适应系统自身的特点、遗传算法的特点以及它们间的相似性,该文提出一种复合多层次遗传算法,分别对复杂适应系统中的模型层、Agent层和参数进行演化优化,以获得能够反应实际情况的复杂适应系统模型。文章最后指出了这一方法的进一步的研究方向。     

Behavioural equivalence in simulation modelling

Discrete event simulation has grown up as a practical technique for estimating the quantitative behaviour of systems, where direct measurement is undesirable or impractical. It is also used to understand the detailed functional behaviour of such systems. Its theory is largely that of experimental science, centering on statistical approaches to validation, rather than on the verification of detailed behaviour. On the other hand, much work has been done on understanding and proving functional properties of systems, using techniques of formal specification and concurrency modelling. This article presents an approach to understanding equivalence of behaviour of discrete event simulation models, using a technique from the concurrency world, Milner’s Calculus of Communicating Systems (CCS). This yields a significant advance over the main previous work, Schruben and Yücesan’s simulation graphs. CCS allows for the use of observational equivalence, which can capture a more flexible, behavioural notion of equivalence than the structural equivalence defined there.A common framework based on the process view of models is constructed, using a hierarchical graphical modelling language (Extended Activity Diagrams). This language is shown to map onto both the major constructs of the DEMOS discrete event simulation language and the corresponding CCS models. A graphically driven tool based on such a framework is presented, which generates both types of models. Using the CCS model, behavioural equivalences and differences in simulation models are demonstrated.     

A set-theoretic model reference adaptive control architecture for disturbance rejection and uncertainty suppression with strict performance guarantees

Research in adaptive control algorithms for safety-critical applications is primarily motivated by the fact that these algorithms have the capability to suppress the effects of adverse conditions resulting from exogenous disturbances, imperfect dynamical system modelling, degraded modes of operation, and changes in system dynamics. Although government and industry agree on the potential of these algorithms in providing safety and reducing vehicle development costs, a major issue is the inability to achieve a-priori, user-defined performance guarantees with adaptive control algorithms. In this paper, a new model reference adaptive control architecture for uncertain dynamical systems is presented to address disturbance rejection and uncertainty suppression. The proposed framework is predicated on a set-theoretic adaptive controller construction using generalised restricted potential functions.The key feature of this framework allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound, and hence, it has the capability to enforce strict performance guarantees. Examples are provided to demonstrate the efficacy of the proposed set-theoretic model reference adaptive control architecture.     

基于HTCPN的工程项目群工作流建模与仿真

在工程项目群实施阶段框架模型构建的基础上, 基于分层赋时着色Petri网定义了工程项目群实施阶段工作流模型。借助CPN Tools仿真平台, 以某工程项目群实施阶段为例进行了实例建模与仿真, 验证了基于分层赋时着色Petri网构建工程项目群实施阶段工作流模型的有效性。该工作流模型能够全面、准确地描述项目群复杂系统的实施全过程, 为实现项目群管理中的进度风险分析和流程优化提供技术与方法的支持。     

复杂仿真系统可信度评估框架研究

关于复杂仿真系统VV&A可信度评估问题,模型可信度层次结构的划分和仿真过程不同阶段对应模型可信度之间的依赖关系,底层模型单元的可信度的确定方法各不同。通过采用贝叶斯网的概念与方法,对复杂建模与仿真系统全生命周期过程的可信度评估框架进行了研究。贝叶斯网的结构可以描述开发过程的每一阶段模型的层次结构以及不同开发阶段对应模型的可信度的依赖关系;节点变量的主观概率值是模型的可信度。通过分析和验证,表明贝叶斯网的可信度评估框架与方法,不但合理、正确而且有效。     

面向服务架构下的SMP2仿真系统动态演化方法

为了支持现实世界与虚拟世界的平行互动演化,满足日益增长的复杂系统动态仿真需求,提出了一个面向服务架构下的SMP2仿真系统动态演化方法。分析了SMP2仿真系统组成及其动态演化分类,提出了一个基于SOA支持动态演化的SMP2仿真系统结构以及SMP2仿真系统动态演化需求模型,设计并实现了两个系统动态演化相关的仿真组件,以卫星导航可见卫星数量演化仿真实验为例验证了方法的可行性,并讨论了下一步的研究方向。     

用于复杂适应系统仿真的Agent免疫学习系统

分析了复杂适应系统（Complex Adaptive System，CAS）仿真中对Agent学习系统的要求以及基于遗传算法的Agent规则学习系统的不足，提出了一种基于改进免疫遗传算法的Agent学习系统，在该算法中将领域知识和经验作为疫苗对规则库中的规则进行免疫按种，并利用混沌变异模型对规则进行变异操作，产生新的规则。最后，结台跨流域调水管理复杂适应系统仿真中的Agent规则学习过程，对Agent的规则学习和演化机制进行了算法验证及实例分析。     

Logic of design actions

The way in which knowledge about design can be incorporated into knowledge-based design systems is discussed and demonstrated within the framework of an overall logical/linguistic model of the design process. The technique of hierarchical planning is discussed. within this framework. The domain under consideration is that of spatial layout in buildings.     

开放式工业自动化控制系统的软件框架

提出了一种用于工业自动化领域的开放式控制系统软件框架,简称OCSIA软件框架。OCSIA软件框架具有层次化结构,从低到高依次是基础驱动层、核心控制层和监管应用层。基础驱动层负责直接驱动包括串口、并口、现场总线等各种接口类型的物理设备,并作为数据服务器,以通道的形式向上层提供硬件无关接口。核心控制层通过通道与基础驱动层通信,实现对物理设备的间接控制;并实时监测系统状态,在系统状态发生异常时,向监管应用层发送报警信息。监管应用层提供系统监管人员与系统的交互接口,方便系统监管人员对系统运行环境的实时监视和控制。通过设计和实现一个传输控制系统的实例模型验证了OCSIA软件框架的正确性和可行性。