Intelligent Control of Servo Motor Drives

This report presents the application of intelligent control in servo motor drives. Firstly, the fuzzy neural network has been introduced. Then the control algorithm of recurrent fuzzy neural network used in linear synchronous motor drive and robust fuzzy-neural-network sliding-mode control for two-axis motion control system has been designed. The simulations and comparative experiments has been conducted in practical systems Gantry-type positioning platform drive control system, five-degree-of-freedom active magnetic bearing (AMB) and six-phase PMSM drive system to verify the the effectiveness of the proposed algorithms.

Faa-Jeng Lin (M’93, SM’99, F’17) received B.S. and M.S. degrees in electrical engineering from National Cheng Kung University, Taiwan, and Ph.D. degree in electrical engineering from National Tsing Hua University, Taiwan, in 1983, 1985, and 1993 respectively. Currently, he is a Chair Professor at the Department of Electrical Engineering, National Central University, Taiwan. His research interests include AC motor drives, power electronics, renewable energies, smart grids, intelligent and nonlinear control theories. His work has been widely cited. Several of his papers have helped to establish research areas such as fuzzy neural network control of motor drives and motion control systems, and resonant converters for piezo-ceramic motor drives. Moreover, he is Associate Editor of IEEE Trans. on Fuzzy Systems and IEEE Trans. on Power Electronics. In addition, he is the chair and principle investigator of Smart Grid Focus Center, National Energy Project Phase I and II in Taiwan, and the Executive Director of Taiwan Power Company. He received the Outstanding Research Awards from the National Science Council, Taiwan, in 2004, 2010 and 2013 and the Outstanding Professor of Engineering Award in 2016 from the Chinese Institute of Engineers, Taiwan. He is also an IET Fellow.