Parameter Estimation and Adaptive Control for Nonlinear Servo Systems (Emerging Methodologies and Applications in Modelling, Identification and Control)

Shubo Wang received his M.S. degree in control science and engineering from the School of Information Science and Engineering, Central South University, Hunan, China, 2011; and Ph.D. degree in control science and engineering from the Beijing Institute of Technology, Beijing, China, in 2017. Since 2017, He has been with the School of Automation, Qingdao University, where he became an associate professor in 2019. He has co-authored one monograph and more than 40 international journal and conference papers. His current research interests include adaptive control, parameter estimation, neural network, servo system, robotic, nonlinear control and applications for robotics and motor driving systems.

Jing Na received his B.Eng. and Ph.D. degrees from the School of Automation, Beijing Institute of Technology, Beijing, China, in 2004 and 2010, respectively. He was a Monaco/ITER Postdoctoral Fellow at the ITER Organization, Saint-Paul-lès-Durance, France, and also a Marie Curie Intra-European Fellow with the Department of Mechanical Engineering, University of Bristol, U.K. Since 2010, he has been with the Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, China, where he became a professor in 2013. He has co-authored one monograph and more than 100 international journal and conference papers. His current research interests include intelligent control, adaptive parameter estimation, nonlinear control.

Xuemei Ren received her B.S. degree from Shandong University, Shandong, China, in 1989, and M.S. and Ph.D. degrees in control engineering from the Beijing University of Aeronautics and Astronautics, Beijing, China, in 1992 and 1995, respectively. She worked at the School of Automation, Beijing Institute of Technology as a professor from 2002. She has published more than 100 academic papers. Her research interests include nonlinear systems, intelligent control, neural network control, adaptive control, multi- drive servo systems and time delay systems.