Self-tuning Controller for Servo Motor with an Adaptive Disturbance Observer

摘要：

In this paper,the state-space disturbance observer was successfully applied to servo motors to estimate and compensate for load variation.Furthermore,an auto-tuning procedure was developed accordingly to identify the varied parameters for state-space disturbance observer of the motor.Then,a real-time IP position controller based on identified parameters is designed by neural network for permanent magnet synchronous motor (PMSM) servo system.The neural networks configuration is simple and reasonable,and the weight has definitely physical meaning.It has rapidly adjusting character to realize the real-time control.The simulation results show that the proposed control scheme not only enhances the fast tracking performance,but also increases the robustness of the servo system.

关键词： disturbance observer identification servosystem self-tuning neural network

作者: Hongkui Li Qinglin Wang

作者单位: School of Science Shenyang Ligong University Shenyang,China Department of Economic Management Liaoning Provincial College of Communications Shenyang,China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 277-281

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）