针对随机扰动现象能够破坏异步电动机调速系统稳定性的问题,本文根据神经网络技术和反步法的原理,对输入饱和的异步电动机随机非线性系统的神经网络速度控制进行研究。考虑异步电动机随机系统中存在的输入饱和限制,利用神经网络来逼近随机系统中不确定的非线性项,并使用自适应反步法构造了异步电动机的自适应神经网络速度调节控制器。同时,利用Matlab软件进行仿真实验。仿真结果表明,本文所提出的自适应神经网络速度控制器,可以快速地跟踪给定的期望速度信号,克服了输入饱和、参数不确定、负载扰动等因素的影响,实现了对异步电动机的有效控制。该研究具有一定的实际应用价值。
Considering the stochastic disturbance may undermine the stability of the induction motor drive system,this article studies speed regulation control of the stochastic induction drive system with input saturation based on neural networks and backstepping.Neural networks are used to approximate the unknown nonlinearities,and backstepping technique is applied to design controllers.And Matlab is used to conduct the simulation.The simulation results show that the proposed adaptive neural network speed controllers can overcome the influences of parameter uncertainties,load disturbance and input saturation and make sure that the proposed approach tracks the given tracking signal well.This study has some value in practical applications.