摘要
基于动态模型提出了一种性能较好的递归模糊神经网络无速度传感器无刷直流电动机控制方法,即采用递归模糊神经网络控制器作为转速控制器来近似最优控制器输出。仿真结果表明,当系统参数动态变化或受到外部不确定因素影响时,利用神经网络来在线调整网络的隶属函数参数以及神经网络递归权值,使系统具有良好的动、静态性能。
A speed-sensorless control method for Brushless DC Motor, which applies recurrent fuzzy neural network （RFNN）, is presented in this paper based on the dynamic model of Brushless DC Motor. The RFNN controller is used as a speed controller to mimic the optimized output of the system. The simulation results show the good performance for the system by using network to adjust the parameters and the recurrent weight of neural network on-line dynamically on the condition of variety of system parameter and the impact of outside uncertainty factors.
出处
《微电机》
北大核心
2007年第2期29-32,共4页
Micromotors
