自适应人工神经网络电机控制器设计

Design of Control Based on Adaptive Artificial Neural Network

提出了一种自适应人工神经网络无刷直流电动机(BLDCM)转速控制器设计方法;针对传统PID调节器难以应对系统超调和短时振荡等问题,提出了一种结合人工神经网络和传统PID控制的新方法;首先建立了(BLDCM)的本体数学模型,在此基础上描述了将人工神经网络和PID控制相结合的模型,并对具体的控制算法进行了定义;最后,使用Matlab仿真工具对BLDCM控制实例进行了仿真;实验结果表明,结合人工神经网络和PID控制器的新控制方法具有响应快、鲁棒性强以及控制精度高等优点,很好地抑制了超调和振荡。

A design method for designing the control of BLDCM based on adaptive artificial neural network and PID control method.Aiming at the traditional PID control can not resolve system over-regulating and oscillation,a new method base on combing the artificial neural network with the traditional PID control method.Firstly,the mathematical model of BLDCM is introduced,and the model combined the artificial network and PID control is advanced,the control method is defined.Finally,the Matlab tool is used to simulate the BLDCM control instance.The result shows the new control method combing the characters of quick response,robustness and high control precision and restraining the over-regulating and oscillation greatly.