西安工业大学“知行讲坛”
讲坛题目：浅谈多智能体系统分布式协调控制
主讲人：郑元世 教授
讲座时间：2021年11月25日，9:30-10:30
讲座地点：工5-404
主办单位：研究生院
承办单位：电子信息工程学院
摘要：This article considers iterative learning control (ILC) for a class of discrete-time systems with full learnability and unknown system dynamics. First, we give a framework to analyze the learnability of the control system and build the relationship between the learnability of the control system and the input–output coupling matrix (IOCM). The control system has full learnability if and only if the IOCM is full-row rank and the control system has no learnability almost everywhere if and only if the rank of the IOCM is less than the dimension of system output. Second, by using the repetitiveness of the control system, some data-based learning schemes are developed. It is shown that we can obtain all the needed information on system dynamics through the developed learning schemes if the control system is controllable. Third, by the dynamic characteristics of system outputs of the ILC system along the iteration direction, we show how to use the available information of system dynamics to design the iterative learning gain matrix and the current state feedback gain matrix. And we strictly prove that the iterative learning scheme with the current state feedback mechanism can guarantee the monotone convergence of the ILC process if the IOCMis full-row rank. Finally, a numerical example is provided to validate the effectiveness of the proposed iterative learning scheme with the current state feedback mechanism.
个人简介：
郑元世，西安电子科技大学教授，博士生导师，华山学者。主要从事多智能体系统的分布式协调与控制、群体行为与群体智能、信息物理系统等研究工作，在多项国家自然科学基金等项目支持下，率先提出了几类异质/切换/混杂多智能体系统，深入研究了其分布式协调控制问题，公开发表SCI检索论文40多篇，其中ESI高被引论文9篇，Google学术引用2300多次。是美国数学评论评论员，中国自动化学会青年工作委员会委员，控制理论专业委员会多智能体系统学组委员，中国系统仿真学会智能系统建模与仿真专业委员会委员；担任IET-The Journal of Engineering的副编辑，40多个国际SCI期刊审稿人。获得国家自然科学奖、教育部自然科学奖，江西省自然科学奖，北京地区广受关注学术论文奖，宁夏自然科学优秀学术论文奖等学术奖励，获陕西省高校“青年杰出人才支持计划”，陕西省科协青年人才托举计划等荣誉称号。
