基于多智能体的城市交通仿真研究

多智能体模型是一种研究社会、经济、生态等复杂系统的动态研究方法,交通系统是一个具有随机性、动态性和自适应性等特征的开放的复杂系统。因此以多Agent技术为手段结合交通系统的组成和复杂性特征,利用基于Agent的计算机仿真通过模拟交通系统中个体的行为,可以让一群这样的个体在计算机所营造的虚拟环境下进行相互作用并演化,自下而上的"涌现"出整体系统的复杂性行为。借助Netlogo软件平台,利用Traffic Grid模型仿真研究了有人参与的交通仿真实验,获取了随着时间变化的车辆平均速度、平均等待时间等数据,根据其变化曲线为建设低碳交通和智能交通系统(ITS)提供决策。     

面向复杂机械产品开发的多Agent系统研究

根据面向复杂机械产品开发的分布式智能决策的设计要求,构建了一种基于多ALgent技术的复杂机械产品开发系统模型.该模型对系统知识进行了分类和有效表述,开发了多个Agent功能模块,通过黑板机制完成不同Agent之间的信息通讯和交互,通过工作流管理实现系统分布式协同工作.研究实例表明,该系统能够有效地分解复杂产品开发的工作流任务,降低复杂产品开发的复杂性和提高开发效率.     

复杂分组交换模块功能仿真验证的方法研究

对复杂分组交换模块仿真验证的复杂性进行了讨论,并分析了四种常用仿真模型的优缺点,在此基础上,提出了基于软硬协同仿真模型的复杂分组交换模块功能仿真验证系统方案,并详细地论述了该系统框架结构和工作流程。通过测试,表明该结构能较好地完成分组交换模块功能仿真的任务。     

基于Agent的供应链运作仿真技术的研究

在给多个智能代理分别赋予生产运作的各种知识，如库存管理、生产计划等之后．通过多个智能代理协同合作，对供应链中企业的生产运作过程进行仿真。在研究该仿真系统的智能代理的内部任务、结构、多代理通讯机制等实现技术基础上，实现了该系统，并给出了一个供应链仿真的结果。     

多传感器机器人的集成开发系统

设计了一个用于多传感器机器人控制的集成开发系统，该系统带有一个智能接口，可以集中采集多个传感器的数据，并进行一部分低层的数据融合处理，系统软件为多传感器的研究提供了必要的仿真工具及其他辅助控制算法，系统通用性好，为基于多感器的智能机器人的研究提供了一个很好的工具。     

多智能体分布式智能控制在VAV空调系统中的应

针对变风量（VAV）空调系统的特性，将VAV系统分解为多个智能体，提出了基于多智能体技术的分布式智能控制方法，有效地解决了变风量空调系统回路间的解耦和协调问题。建立了VAV系统的动态仿真程序，仿真结果表明该控制方法是有效的。     

基于智能配线的通用飞机航电试验技术研究

为解决通用飞机复杂航电系统的集成和测试难题,研究一种在数字仿真基础上基于智能配线的航电系统集成与测试方法。基于增量式的系统集成策略分析,对航电系统的集成特点进行研究,进而对其进行分级分步处理,并提出真件逐步替代仿真件的系统集成方法。对航电系统激励响应式的传统测试方法特性进行研究,提出在测试序列基础上的基于智能配线的自动化测试,进而得出航电系统动态综合测试方法。AG600飞机航电系统集成与测试的应用结果表明:所提出的方法及平台能够大大提高航电系统集成与测试的效率。     

智能车载系统的音乐服务与交互设计研究

目的探讨智能车载系统中的音乐服务与交互设计。方法基于对智能车载系统信息复杂性的探讨,结合未来车联网下可连接的服务系统,分析车载系统中音乐服务所需的交互设计要素。结论通过搭建基于云服务的信息服务系统,定义了智能车载系统中音乐服务的服务模型以及其人机交互界面,并通过应用实例初步验证了研究的有效性及可行性。     

基于有限元和系统辨识的智能结构主动控制

探讨了一种压电智能结构的设计方法,包括动力学建模、控制器设计和闭环系统有限元仿真。首先采用有限元方法计算滤过白噪声激励下压电智能结构的响应,以此响应作为系统辨识方法的输入,采用基于观测器/K a lm an滤波器的系统辨识方法(O bserver/K a lm an filter iden tification,OK ID)得到系统的M arkov参数,亦即单位脉冲响应的采样值,然后采用特征系统实现算法(E igensystem R ea lization A lgorithm,ERA)得到系统的最小实现,基于此模型采用LQG优化算法设计鲁棒控制器,并将反馈控制引入有限元模型进行闭环系统仿真,根据仿真结果评价设计方案。此方法克服了有限元模型无法直接用于控制器设计的缺点,通过将反馈控制引入有限元模型,可用有限元方法研究控制器的性能,也适用于设计其它复杂智能结构。     

汽车电动助力转向系统负载阻力矩特性多自由度建模仿真分析

为了研究由道路、轮胎以及车辆等多元素组成的非线性复杂系统中电动助力转向系统(EPS)受力状态，从EPS系统齿轮齿条转向机构入手，结合统一轮胎模型、车辆七自由度动力学模型以及前轮定位参数，建立基于七自由度整车转向模型的EPS系统负载阻力矩模型，并通过MATLAB/Simulink软件进行多自由度建模仿真，最后进行双移线仿真实验和转向瞬态响应仿真实验。实验结果表明：与三自由度整车转向模型相比，该模型能更好地反映在不同车速下，汽车EPS系统负载阻力矩随转向盘转角的变化特性。     

Assessing operational complexity of manufacturing systems based on statistical complexity

The aim of this paper is to contribute to complex systems thinking in manufacturing organisations through the development of a metric for operational complexity. Operational complexity is concerned with the temporal aspects of coordination and control in manufacturing systems. Statistical complexity from computational mechanics theory is proposed as the metric. The metric can potentially be used to support decision making by objective assessment of complexity. The properties of the metric are explored through simulation studies. The simulation results confirm that the proposed metric captures the intuitive notion of complexity. It is shown that operational complexity is influenced by internal factors such as system structure, as well as external ones such as demand, and that complexity can be managed through the application of appropriate control methods. A case study is presented that applies the metric to real production data. The case study shows that the global recession had resulted in a decreased operational complexity of outputs.     

复杂长距离输水系统仿真优化研究

将自优化模拟模型应用于长距离输水系统优化调度研究中，以数字仿真模型为基础，增加在线控制优化环节，根据仿真模型的输出反馈不断优化系统输入，实现系统仿真过程的自适应优化。并以MATLAB软件作为系统仿真平台，成功地实现了实例工程的仿真优化过程，为复杂长距离输水系统优化调度研究开辟了一条新途径。     

An agent-based multilayer architecture for bioinformatics grids

Due to the huge volume and complexity of biological data available today, a fundamental component of biomedical research is now in silico analysis. This includes modelling and simulation of biological systems and processes, as well as automated bioinformatics analysis of high-throughput data. The quest for bioinformatics resources (including databases, tools, and knowledge) becomes therefore of extreme importance. Bioinformatics itself is in rapid evolution and dedicated Grid cyberinfrastructures already offer easier access and sharing of resources. Furthermore, the concept of the Grid is progressively interleaving with those of Web Services, semantics, and software agents. Agent-based systems can play a key role in learning, planning, interaction, and coordination. Agents constitute also a natural paradigm to engineer simulations of complex systems like the molecular ones. We present here an agent-based, multilayer architecture for bioinformatics Grids. It is intended to support both the execution of complex in silico experiments and the simulation of biological systems. In the architecture a pivotal role is assigned to an "alive" semantic index of resources, which is also expected to facilitate users' awareness of the bioinformatics domain.     

Monte Carlo-based assessment of system availability. A case study for cogeneration plants

The complexity of the modern engineering systems besides the need for realistic considerations when modeling their availability and reliability render analytic methods very difficult to be used. Simulation methods, such as the Monte Carlo technique, which allow modeling the behavior of complex systems under realistic time-dependent operational conditions, are suitable tools to approach this problem.The scope of this paper is, in the first place, to show the opportunity for using Monte Carlo simulation as an approach to carry out complex systems' availability/reliability assessment. In the second place, the paper proposes a general approach to complex systems availability/reliability assessment, which integrates the use of continuous time Monte Carlo simulation. Finally, this approach is exemplified and somehow validated by presenting the resolution of a case study consisting of an availability assessment for two alternative configurations of a cogeneration plant.In the case study, a certain random and discrete event will be generated in a computer model in order to create a realistic lifetime scenario of the plant, and results of the simulation of the plant's life cycle will be produced. After that, there is an estimation of the main performance measures by treating results as a series of real experiments and by using statistical inference to reach reasonable confidence intervals. The benefits of the different plant configurations are compared and discussed using the model, according to their fulfillment of the initial availability requirements for the plant.     

无线通信系统仿真中的性能指标的测量

面向3G和4G的下一代无线通信系统复杂性远高于传统系统，基于经验法则的传统设计方法具有较大的局限性，理论仿真支撑的网络规划和系统仿真显得尤为重要。近年来计算机软件仿真技术和无线通信数学模型已渐趋成熟，目前无线通信系统的设计标准化流程一般是从软件仿真开始。特别是对于3G和4G无线系统，由于系统复杂性的提高，在系统设计和规划阶段必须首先在仿真环境中测量各项系统性能指标。本文首先介绍基于MATLAB的无线通信系统仿真技术和无线通信仿真系统的常用测量指标，然后通过搭建基于DCA算法的无线通信仿真系统在软件环境中测量了相关的性能指标。文章最后利用该测试手段结合DCA算法在不均衡用户分布环境中的性能表现的实例给出了软件仿真结果和仿真数据分析。     

Development of a real-time multi-objective scheduler for a semiconductor fabrication system

Semiconductor wafer fabrication involves possibly one of the most complex manufacturing processes ever used. This causes a number of decision problems. A successful system control strategy would assign appropriate decision rules for decision variables. Therefore, the goal of this study is to develop a scheduler for the selection of decision rules for decision variables in order to obtain the desired performance measures given by a user at the end of a certain production interval. In this proposed methodology, a system control strategy based on a simulation technique and a competitive neural network is suggested. A simulation experiment was conducted to collect the data containing the relationship between the change of decision rule set and current system status and the performance measures in the dynamic nature of semiconductor manufacturing fabrication. Then, a competitive neural network was applied to obtain the scheduling knowledge from the collected data. The results of the study indicate that applying this methodology to obtaining a control strategy is an effective method considering the complexity of semiconductor wafer fabrication systems.     

基于数据驱动仿真的两设备系统元模型

半导体封装测试系统等复杂制造系统的性能分析是项非常困难的任务。利用仿真模型构建两设备系统元模型,并以元模型为基石构建面向大规模复杂系统的近似解析方法是分析复杂制造系统的有效手段。为了快速准确地构建两设备系统元模型,提出了一种基于数据驱动仿真技术及人工神经网络的元模型构建方法。该方法以考虑缓存输送时间的两设备制造系统为研究对象,采用AREAN的二次开发技术实现仿真模型的自动配置、运行、统计,以生成人工神经网络所需案例,并通过比较分析BP、RBF和Chebyshev这3类典型的函数逼近神经网络确定最优的人工神经网络模型。实验结果表明径向基函数密度为120的RBF神经网络模型表现最优,其结果误差最小,能够成为大规模复杂制造系统近似解析方法的基石。