Date: 18 October 2024, Friday
Time: 4:30 pm
Venue: YEUNG-B5311, City University of Hong Kong
Zoom Meeting ID: 859 2865 1236
Password: 123456
Speaker: Dr Zhaobo Liu, Shenzhen University
Optimal adaptive output regulation for discrete-time nonlinear stochastic systems
Dr Zhaobo Liu, Shenzhen University
Abstract: In this presentation, we address the output regulation problem associated with a basic class of discrete-time nonlinear stochastic systems with unknown parameters. We allow the controlled plant to exhibit highly nonlinear growth, as well as nonlinearly parameterized structures in the exosystem. Our main purpose is to design an adaptive regulator to achieve the optimal performance of the regulated output. The design of the regulator is an integration of the recursive least squares estimator and a modified nonlinear least squares (NLS) algorithm. Under certain mild conditions, it is shown that with stable exosystems, the square of the norm of the closed-loop regulated output is asymptotically optimal in the average sense almost surely. Specifically, we propose a new formula for the strong convergence rate of NLS and derive an almost optimal strong convergence rate of the proposed modified NLS algorithm. Additionally, we employ novel closed-loop analysis techniques to overcome the Bayesian assumptions required in existing research on the stabilizability of discrete-time nonlinear stochastic systems.
Speaker’s Bio:Zhaobo Liu is currently an Assistant Professor at the Institute for Advanced Study, Shenzhen University. He received the B.Sc. degree from the School of Mathematical Sciences, Peking University, in 2015, and the Ph.D. degree from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, in 2020. His current research interests include adaptive control, data science, and computational intelligence.
WEBINAR WEBSITE:
http://cccn.ee.cityu.edu.hk/webinar/
