讲座题目：Iterative Learning Control and Applications in Rehabilitation Robots

报告人：Dr. Ying Tan

时 间：9月16日（周四）下午2:30
地 点：力学楼434会议室
主持人：王金枝(教授)

报告内容摘要：
     Iterative learning control (ILC) is a methodology which aims to provide accurate tracking of a trajectory that is repeated. ILC has a mature theoretical background and has been applied to a variety of control applications including robotics, rotary systems, batch/factory/chemical processes, bio/artificial muscle, actuators, semiconductor and power electronics. ILC has been proven to be appropriate for stroke patients’ repeated ‘trials’ of a movement task. In most ILC algorithms reported in the literature, the constraints on the inputs/outputs/states are always ignored. In this talk, dual ILC loops as well as the reference governor are employed to deal with input saturation. The proposed algorithms will be tested in rehabilitation robots soon.

报告人简介：
      Dr. Ying Tan received her Bachelor from Tianjin University, China in 1995. In 1998, she joined the National University of Singapore and finished her PhD study in 2002. She joined McMaster University in 2002 as a postdoctoral fellow in the Department of Chemical Engineering. She has started her work in the Department of Electrical and Electronic Engineering, the University of Melbourne since 2004. Currently Dr. Ying Tan is a senior lecturer in the Department of Electrical and Electronic Engineering, the University of Melbourne. She is also a Future Fellow under Australian Research Council. Her research interests are in intelligent systems, nonlinear control systems, model predictive control, real time optimization, sampled-data distributed parameter systems and formation control.