复合自抗扰在三电机同步控制系统的应用

Compound active disturbance rejection applied in three-motor synchronous control system

针对自抗扰控制器(ADRC)算法复杂、参数多且调节耗时耗力的问题,对ADRC结构进行优化的基础上,设计了基于径向基函数(RBF)神经网络的复合ADRC。该控制器利用RBF神经网络实现对被控对象的在线跟踪,获得ADRC参数的在线调整信息,从而实现ADRC参数的在线自调节功能,并将此方法运用于三电机同步控制系统,结合西门子S7-300 PLC构建实验平台,在PLC上实现基于RBF神经网络的复合ADRC控制算法进行速度控制实验,实验结果表明该方法不仅能实现部分参数的自调节功能,而且能使超调量降到最低甚至实现速度的无超调调节,提高了系统的动态性能和稳态精确度。实验结果证明了该方法具有实际应用性。

For problems of complex algorithm, multi parameter and labor intensive and time consuming adjustment in the active disturbance rejection controller（ADRC）, on the basis of optimizing the structure of ADRC, a compound ADRC based on radical basis function（RBF） neural network was designed. The controller obtained the online adjustment information of ADRC parameters by using RBF neural network to track the controlled object online, so that the parameters of the ADRC can be automatically adjusted. The method was applied in the three motor synchronous control system which combined with S7 300 PLC to build an experimental platform and adopted PLC programming language for algorithm implementation in order to perform experiments of the speed control. The results show that the method can achieve the self adjusting function of partial parameters and can decrease overshoot to the lowest and even realize speed regulation without overshoot. It can also improve the dynamic performance and steady state accuracy of the system. The experimental results show that the method has practical application.