Title:  Advanced Intelligent Adaptive Control of Uncertain Nonlinear Systems

Abstract: Due to the existence of uncertainties, external disturbances, and limited available information in system dynamics, traditional adaptive control is always difficult to achieve satisfactory control performance of the overall system. Intelligent adaptive control has proved to be very efficient in dealing with complex systems, where neural networks, fuzzy logic systems, and reinforcement learning are often employed. This report presents some new results of advanced intelligent adaptive control towards uncertain nonlinear systems, which covers asymptotic control, fault-tolerant control, optimized control, and data-driven control. On the one hand, based on artificial intelligence techniques, some new control theory and advanced control strategies with efficiency consideration are established for uncertain nonlinear systems. On the other hand, simulations to typical nonlinear systems are also included.

Biography: Yuan-Xin Li received the B.S. degree in mathematics and applied mathematics from Qufu Normal University, Jining, China, in 2007, the M.S. degree in computational mathematics from the College of Mathematical Sciences, Dalian University of Technology, Dalian, China, in 2009, and the Ph.D. degree in control theory and control engineering from the College of Information Science and Engineering, Northeastern University, Shenyang, China, in 2017. He is currently a Professor with the Department of Science, Liaoning University of Technology, Jinzhou, China. His research interests include adaptive fuzzy/neural control, fault-tolerant control, event-triggered control, and adaptive control of cyber-physical systems. He has authored or co-authored over 100 journal papers.