摘要
由于无刷直流电机控制系统是多变量和非线性的,针对传统PID控制方法的不足,提出一种基于径向基函数RBF(Radial Basis Funct ion)神经网络在线辨识的单神经元PID自适应控制方法,并用于无刷直流电机的控制中。构造了一个径向基函数神经网络对系统进行在线辨识、建立在线参考模型,由单神经元控制器完成控制器参数的自学习,并在数字信号处理器中实现控制参数的在线调节。系统较好地实现了给定速度参考模型的自适应跟踪,结构简单,能适应环境变化,具有较强的鲁棒性。
Because the brushless DC motor was a multi-variable and non-linear system, this paper presented a novel approach of single neuron PID adaptive control for brushless DC motors based on RBF neural network on-line identification in virtue of the disadvantage of conventional PID control. A RBF network built to identify the system on-line. It constructed the on-line reference model. Self-learning of controller parameters implemented by single neuron controller. And a digital signal processor used to fully prove the flexibility of the control scheme in real time. Excellent flexibility and adaptability as well as high precision and good robustness were obtained by the proposed strategy.
出处
《微电机》
北大核心
2008年第10期94-97,共4页
Micromotors
