基于模糊RBF神经网络的无刷直流电机调速控制

Speed Control of Brushless DC Motor Based on Fuzzy RBF Neural Network

针对无刷直流电机的速度控制,把模糊控制与神经网络原理相结合,提出了基于模糊RBF神经网络的PID控制方法,该网络具有自适应性。利用最小均方差来调整网络的权值,使径向基函数快速收敛,获得较佳PID控制参数,达到对转速跟随控制。同时自适应网络对整个系统的动态性能起到了改善作用。仿真结果表明该方法具有很好的控制效果。

Targeted at the speed control system of the brushless DC motor（BLDCM）,the PID control method based on self-adaptability fuzzy RBF neural network was proposed according to fuzzy control combined with neural network principle.The weights of network adjusted by using the least mean square made fast convergence of radial basis function to obtain better PID control parameters and achieve the speed tracked control.The self-adaptability network could improve the dynamic performance of the whole system.The simulation result shows that the method has great control effect.