Speed-regulation System of PMLSM Based on BP Neural Network PID Control

摘要：

　　For the characteristics of permanent magnet linear synchronous motor (PMLSM) hoisting systems nonlinear,time-varying and vulnerable to disturbance,based on the established PMLSM d-q axis dynamic model,designed of an improved BP neural network PID speed controller.Modified the fixed learning rate in BP neural network to adaptive adjustable,and added the momentum to reduce the oscillation tendency in the learning process,greatly improved the convergence speed and avoided the network into a local minimum.Compared with the simulations of traditional PID and the improved BP network PIE) speed controller,the results showed that the improved BP neural network PIE) speed controller had the high quality and it can make the system with better dynamic performance and robustness.

关键词： PMLSM dynamic model BP neural network PID control speed-regulation system

作者: Fuzhong Wang Qiongxia Yu

作者单位: College of Electrical Engineering and Automation;Henan Polytechnic University;Jiaozuo,China

会议类型: 国际会议

会议名称: 2012 International Conference on Intelligent System and Applied Material(2012智能系统与应用材料国际会议)(GSAM2012)

会议地点: 太原

会议语种:英文

页码: 1217-1221

在线出版日期: 2012-01-13（万方平台首次上网日期，不代表论文的发表时间）