基于鲸鱼算法小波神经网络PID的PMSM转速控制

针对永磁同步电机交流伺服系统的非线性特征和不确定扰动等问题，以及传统PID控制器的线性局限性，提出基于鲸鱼优化算法的小波神经网络PID的转速控制策略。采用小波神经网络与PID控制器结合的方式，构成永磁同步电机的转速控制器，同时利用鲸鱼优化算法对学习速率和惯性系数进行优化，从而达到对神经网络权值的进一步优化。通过实验结果表明，本文所提控制策略得到的电机稳定时间是0.025 s,最大超调量是52 r/min,施加转矩之后的转速误差为0.002,因此本文控制策略的动态性能和抗干扰能力具有一定优势。

Speed control of PMSM based on WOA wavelet neural network PID

Aiming at the nonlinear characteristics and uncertain disturbance of the AC servo system of permanent magnet synchronous motor, as well as the linear limitations of traditional PID controllers, a speed control strategy based on the wavelet neural network PID based on whale optimization algorithm is proposed. The wavelet neural network and incremental PID controller are combined to form the speed controller of permanent magnet synchronous motor, and the whale optimization algorithm is used to further optimize the parameters. The experimental results show that the stability time obtained by the proposed method is 0.025 s, the maximum overshoot is 52 r/min, and the speed error after applying torque is 0.002, so the dynamic performance and anti-interference ability of the control strategy in this paper have certain advantages.