摘要
为解决永磁同步电动机位置伺服系统控制优化问题,针对离跟踪目标较远、较近及扰动情况下动态响应和静态稳定性能之间的矛盾,提出设计变增益函数应用于系统的小波神经网络反推控制策略。分析了反推控制器参数增益对系统跟踪误差的影响,使用新的变增益函数实现系统控制精度和动态响应的优化。为实现系统在扰动下良好的动静态性能,由系统三个控制环响应速度的差异,利用小波神经网络来分别逼近转速环和电流环的非线性扰动项,并采取自适应技术对逼近误差进行补偿。仿真结果表明,上述研究为永磁同步电机位置伺服系统实现系统动态响应性能和稳定控制精度提供了科学依据。
In the paper, a variable gain function, with Adaptive Wavelet Neural Network Back - stepping control method, was designed to improve the static and dynamic performance of permanent magnet synchronous motor （PMSM） position servo system at the condition of large or small tracking error or being disturbed. By analyzing the effect from the parameter＇s gain of the back - stepping controllers to the error of the position tracking system, the designed new variable gain function was used to solve the conflict between the system＇s precision and response speed. Also the Wavelet Neural Network（WNN）, for the control of speed and current respectively, and adaptive method for the approximation error were applied to evaluate the nonlinear disturbances of the system to achieve stronger robustness. Compensation was done with the constant controller parameters of back - stepping control, the theoretical analysis and simulation results show the stepping precision and the response speed of the position control system.
出处
《计算机仿真》
CSCD
北大核心
2016年第4期368-372,共5页
Computer Simulation
基金
国家青年科学基金项目(51407131)
武汉科技大学大学生科技创新基金(14ZRB134)
