Title: Intelligent Adaptive Control of Nonlinear Servo Systems 

Abstract:  The servo system is the core component of the motion control systems to achieve high-speed, high-precision and reliable operation. The modern servo system is developing towards complexity, modularization and intelligence, and it puts forward higher requirements for the rapidity, accuracy and reliability of the control system. However, the servo system has the characteristics of unknown parameters, inaccurate model and strong nonlinearity, which brings severe challenges to the control system design. The intelligent adaptive control, combining the advantages of intelligent learning and adaptive control, is considered to be one of the effective methods to solve the control problems of nonlinear uncertain systems, but the current intelligent adaptive control theory for servo systems has many challenges, such as the difficulty of precise compensation of nonlinear uncertainties and the difficulty of quantitative analysis of dynamic performance, etc. This report will briefly introduce the research work and preliminary results of the research group on intelligent adaptive control of nonlinear servo systems. 

Biography: Qiang Chen received the Ph.D. degree in control science and engineering from Beijing Institute of Technology, Beijing, China, in 2012. Since 2012, He has been with the College of Information Engineering, Zhejiang University of Technology (ZJUT), Hangzhou, China. He is currently a Full Professor and the director of the institute of data-driven control and learning systems in ZJUT. He has presided over 3 National Natural Science Foundation of China (NSFC) projects including National Natural Science Fund for Excellent Young Scholars in 2022, and 1 Key Program of Natural Science Foundation of Zhejiang Province. He has published over 50 academic papers in IEEE Transactions and international journals, and has been authorized more than 40 invention patents, 12 of which were transferred. His research interests include adaptive control and learning control with applications to motion control systems.