一、课程基本信息课程代码：F032513 课程名称（中文）：离散事件系统课程名称（英文）：Modeling, Evaluation and Optimization of Discrete Event Dynamic Systems学分/学时： 2/36 课程讨论时数(小时)：32课程实验数(小时)：4 开课时间：（春；秋；或春，秋）春课程类别：（硕士生学位课；硕士生非学位课；博士生专业课；研究生公共课）开课院系：自动化系任课教师（姓名/工号）：7993预修课程：Probability Theory, Operational Research, Automatic Control Principle面向专业：控制科学与工程二、课程内容简介（宋体小四，加粗）（简要介绍本课程讲授内容，分中、英文对照两部分。宋体小四，1.5倍行距）中 文：Abstract：Over the past few decades, the rapid evolution of computing, communication, and sensor technologies has brought about the proliferation of "new" dynamic systems, mostly technological and often highly complex. Examples are all around us: computer and communication networks; automated manufacturing system; air traffic control systems; highly integrated command, control and communication and information(C3I) systems; advanced monitoring and control systems in automobiles or large buildings; intelligent transportation systems; distributed software systems; and so forth. A significant portion of the activities in these systems, sometime all of it, is governed by operational rules designed by humans; their dynamic therefore characterized by asynchronous occurrences of discrete events, some controlled (like hitting a keyboard key, turn a piece of equipment "on", or send a massage packet), some not (like a spontaneous equipment failure or a packet loss), some observed by sensors and some not. These features lend themselves to the term discrete event system for this class of dynamic systems.The mathematical arsenal centered around differential and difference equipment that has been employed in systems and control engineering to model and study the time-driven processes governed by law of nature is inadequate or simply inappropriate for discrete event systems. The challenge is to develop new modeling frameworks, analysis techniques, design tools, testing methods, and systematic control and optimization procedures for this new generation of highly complex systems. In order to face this challenge we need a multidisciplinary science. First, we need to build on the concepts and techniques of system and control theory (for performance optimization via feedback control), and computer science (for modeling and verification of event-driven processes), and operational research (for analysis and simulation of stochastic model of discrete event systems). Second we need to develop new modeling frameworks, analysis technique, and control procedures that are suited for discrete event systems. The study of discrete event dynamic systems (DEDS) has become rapidly popular among researchers in system and control, in communication networks, in manufacturing, and in distributed computing. This development has also created problems for researchers and especially potential researchers. The first problem is the employed language, formalisms, and approaches, which makes it very difficult to determine the commonalities and distinctions among the competing approaches. The second problem, arises from the different traditional, values, and experience that scholar bring to their study of DEDS, depend on whether they come from control, communication, computer, mathematical logic. In fact, DEDS is conception come from control discipline.The purpose of this course was to provide a few fundamental methods and tools, and some applications that arise from different disciplines, in order to be able to analyze, study and/or practise actual DEDS instances among Ms and PhD level students.

Over the past few decades, the rapid evolution of computing, communication, and sensor technologies has brought about the proliferation of "new" dynamic systems, mostly technological and often highly complex. Examples are all around us: computer and communication networks; automated manufacturing system; air traffic control systems; highly integrated command, control and communication and information(C3I) systems; advanced monitoring and control systems in automobiles or large buildings; intelligent transportation systems; distributed software systems; and so forth. A significant portion of the activities in these systems, sometime all of it, is governed by operational rules designed by humans; their dynamic therefore characterized by asynchronous occurrences of discrete events, some controlled (like hitting a keyboard key, turn a piece of equipment "on", or send a massage packet), some not (like a spontaneous equipment failure or a packet loss), some observed by sensors and some not. These features lend themselves to the term discrete event system for this class of dynamic systems.The mathematical arsenal centered around differential and difference equipment that has been employed in systems and control engineering to model and study the time-driven processes governed by law of nature is inadequate or simply inappropriate for discrete event systems. The challenge is to develop new modeling frameworks, analysis techniques, design tools, testing methods, and systematic control and optimization procedures for this new generation of highly complex systems. In order to face this challenge we need a multidisciplinary science. First, we need to build on the concepts and techniques of system and control theory (for performance optimization via feedback control), and computer science (for modeling and verification of event-driven processes), and operational research (for analysis and simulation of stochastic model of discrete event systems). Second we need to develop new modeling frameworks, analysis technique, and control procedures that are suited for discrete event systems. The study of discrete event dynamic systems (DEDS) has become rapidly popular among researchers in system and control, in communication networks, in manufacturing, and in distributed computing. This development has also created problems for researchers and especially potential researchers. The first problem is the employed language, formalisms, and approaches, which makes it very difficult to determine the commonalities and distinctions among the competing approaches. The second problem, arises from the different traditional, values, and experience that scholar bring to their study of DEDS, depend on whether they come from control, communication, computer, mathematical logic. In fact, DEDS is conception come from control discipline.The purpose of this course was to provide a few fundamental methods and tools, and some applications that arise from different disciplines, in order to be able to analyze, study and/or practise actual DEDS instances among Ms and PhD level students.