报告时间：2021年5月14日（周五）下午16：00

报告地点：37000gcom威尼斯3B205学术报告厅

报告题目：An Experience Replay Based Adaptive Disturbance Observer for a Class of Nonlinear Systems

In this talk, we consider a class of nonlinear systems with unknown disturbances where the disturbance is assumed to be generated by some unknown dynamics. we first use a filtered regressor approach to model the nonlinear systems and the disturbance. We show that this filtered regressor form allows us to estimate the disturbance using only measured state. Next, to improve convergence speed we propose a new adaptive observer with experience replay to ensure that disturbance estimate error is globally exponentially stable. Compared to the existing results, we neither use the knowledge of the disturbance dynamics nor the state derivatives in our adaptive protocol.

报告人：Zhitao Li

Zhitao Li is currentlyPHDcandidatein Nanjing University of Science andTechnology. He is a visiting scholar atMichigan State University in 2019.9-2021.3. His current research interests includeMulti-AgentSystem, Nonlinear Adaptive Control Systems, Finite-timeControl, Concurrent Learning, Reinforcement Learning.