基于蚁群优化的异步电机矢量控制系统的研究

异步电机在运行过程中，由于温度升高、磁路饱和、频率变化等因素的影响，电机的机电参数会发生变化，直接改变的是电机对象的模型，影响控制精度。为了得到更好的控制效果，本文采用在线辨识及在线优化控制器参数的方法，得到了较好的动态特性和稳态精度。应用Simulink设计基于在线辨识及蚁群优化的异步电机矢量控制系统，并进行仿真研究，结果证明了此种方法的有效性，不仅可以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稳态特性，表现出较强的自适应性与鲁棒性。

On Vector Control of Induction Motor Based on Online Identification and Ant Colony Optimization

During operation,due to changes of temperature,magnetic field,frequency and other factors,electrical and mechanical parameters of induction motor will change.h will affect its model and control accuracy directly.In order to obtain better dynamic performance and steady state accuracy,this paper poses a combination method of online identification and online optimization of the controller parameters. Based on online identification and ant colony optimization, a vector control system of induction motor is designed.The simulation results have proved the effectiveness of this method.It can not only meet the timely requirements of induction motor vector control system but also can greatly improve the induction motor dynamic performance and steady state characteristics, showing strong self-adaptability and robustness.