基于神经网络的永磁同步电机的鲁棒控制

提出一种基于神经网络的永磁同步电机的鲁棒控制策略·基于此策略设计了神经网络PID速度控制器,使速度控制器能实时在线调整,由一种混合型神经网络作为辨识器,利用神经网络的学习特性实现对永磁同步电机系统不确定性的鲁棒控制·为了加快响应速度,提高响应性能,采用多步预测性能指标函数下的反传算法·仿真和实验结果表明,所提出的控制方法明显优于一般永磁同步电机系统的控制方法,具有较强的鲁棒性·

Neural-Network-Based Robust Control of PM Synchronous Motor

A neural network based robust control scheme for PM synchronous motor was proposed. This scheme consists of a neural network PID speed controller and a hybrid neural network identificator. The parameters of speed controller can be regulated on line by training neural networks. This realizes robust control for uncertainties of PM synchronous motor driven system. In order to pick up speed of system response and improve system performance,back propagation algorithm under multi step predictive index function was used to train neural network PID controller. The proposed control scheme has stronger robustness and better performance than the conventional control scheme.