PMLSM Controller Design Based on Self-Constructing Feedback Fuzzy Neural Network
Self-constructing feedback fuzzy neural network controller (SCFFNNC) is designed to aim at the parameter uncertainties for permanent magnet linear synchronous motor (PMLSM) since they cause negative influence to the dynamic performance of PMLSM servo system. The thought about self-constructing, in which the number of neurons for the whole structure can be able to increase on line according to the variety of error, is introduced based on combining the non-linear identification of fuzzy control with self-learning of neural network. It can reserve the self-learning abilities, improve the real-time performance for neural network and then enhance the dynamic performance of PMLSM. The simulation results show that the servo system for PMLSM based on SCFFNNC can realize quick response, high precision and strong robustness for the parameter uncertainties of PMLSM.
Self-constructing Feedback Fuzzy Neural Network PMLSM Motor Position Control
Wang Limei Zuo Tao Wu Zhitao
School of Electric Engineering, Shenyang University of Technology, Shenyang 110178
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
3146-3150
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）