【科研动态】学术报告预告二

人:李雪芳

报告时间:2017112日(星期四) 下午15:00-16:00

报告地点:C516

参加人员:全校师生

报告题目:Iterative learning control for systems with non-uniform trial lengths

报告人简介

李雪芳,女,博士。20168月于新加坡国立大学电子与计算机工程系获得工学博士。自20169月至今工作于英国帝国理工学院电子与电气工程系。目前主要研究兴趣包括控制理论、机器人的运动控制、多智能体协作控制、以及混合动力汽车动力系统建模与能源管理。已在《IEEE TAC》、《IEEE TIE》、《Systems & Control Letters》、《Int. J. Robust Nonlinear Control》等国际著名期刊上发表论文近二十余篇,并合作出版专著一部。曾主持或参与的项目有:浙江大学工业控制技术国家重点实验室合作项目, 国家自然科学基金(面上项目),以及由新加坡国家国防科技局、新加坡淡马锡国家实验室、英国工程与自然研究理事会等机构资助的科研项目。

 

Abstract: Iterative learning control (ILC) is an effective control strategy for trajectory tracking of uncertain systems that operate repetitively. In traditional ILC, it is required that the system must repeat strictly on a fixed time interval, which hinders its applicability in practical systems. Motivated by this fact, our work is to extend ILC to systems with randomly varying trial lengths. To deal with the random trial lengths, one of our key technique is to introduce a stochastic variable satisfying the Bernouli distribution to make the expression uniform. Furthermore, in order to compensate the missing information or signals caused by the non-uniform trial lengths, ILC schemes equipped with iteration average operators are presented. Finally, the convergence of the ILC schemes will be derived by virtue of the contraction-mapping methodology. In the end, numerical examples are also presented demonstrate the performance and the effectiveness of the averaging ILC schemes.