基于自适应PID控制器的异步电机矢量控制

为了克服传统PID控制器自适应性及鲁棒性相对较差的缺点。实现高性能的异步电机矢埴控制，提出了采用人工神经网络技术构造自适应PID控制器。在保证调速系统全局快速收敛的情况下，运用有监督的Delta学习规则和合理的控制算法。实现自适应PID控制器参数的在线自动调整。应用MATLAB软件设计基于自适应PID控制器的异步电机矢量控制模型并进行仿真研究，结果表明，自适应PID控制器不仅能够满足异步电动机矢量控制的实时性要求。而且可以大大改善异步电动机的动态性能与静态性能，表现出较强的自适应性与鲁棒性，因而可以取代传统PID控制器以实现高性能的异步电动机矢量控制。

Asynchronous motor vector control based on self-adaptive PID controller

A self-adaptive PID controller based on artificial neural network technology is brought forward to overcome the shortcomings of the traditional PID controller that is relatively weak in self-adaptability and robustness,and to achieve a vector control by an asynchronous motor with high performances.The supervisory Delta study rules and reasonable control algorithms were adopted to automatically fulfill the on-line parameter adjustment of the self-adaptive PID controller in the assurance of an overall and fast convergence of the asynchronous motor driving system.The MATLAB software was used to establish the asynchronous motor vector-controlling model based on the self-adaptive PID controller to carry out a simulation investigation.The results show that the self-adaptive PID controller,which has relatively high self-adaptability and robustness,can satisfy the requirement for time-reality of the asynchronous motor vector control,and greatly improve the dynamic and static performances of the asynchronous motors.Thus the traditional PID controllers can be substituted to realize asynchronous motor vector-control with high performances.