永磁同步电机的改进对角递归神经网络PI控制策略

For the problem that the permanent magnet synchronous motor AC servo system with traditional PI controller cannot strike a balance between good response performance and strong robustness, a control algorithm combining diagonal recurrent neural network (DRNN) and PI control was proposed. In addition, the idea of dynamic adjustment of the learning rate was introduced to improve the algorithm, which solves the problem that the DRNN algorithm cannot strike a balance between system stability and fast learning rate. The simulation model was constructed, and the comparison experiment between PI controller, DRNN-PI controller with fixed learning rate and DRNN-PI controller with variable learning rate was carried out. The experiment shows that the AC servo system using DRNN-PI controller with variable learning rate has a good speed performance. There is no overshoot in the speed curve, and the speed is not affected by load fluctuation.