基于模糊RBF神经网络PID算法的无刷直流电机控制

Application of Fuzzy RBF Neural Network PID Controller in Motion Control Technology of High Voltage Circuit Breaker

高压断路器永磁无刷直流电机操动机构采用直流电机驱动断路器连杆,推动动触头运动,完成分、合闸操作,具备良好的快速响应能力和控制性能。文章构建了无刷直流电机操动机构控制系统仿真模型,详细分析了模糊RBF神经网络PID控制算法以及数学模型。分别用传统PID与模糊RBF神经网络PID控制策略,对高压断路器动触头运动特性控制过程进行了仿真。仿真结果表明,模糊RBF神经网络PID控制器能够较好地实现动触头的速度跟踪控制,使其按照给定运动速度特性曲线动作,实现对断路器动触头的准确控制,证明了模糊RBF神经网络PID控制策略在配有无刷直流电机的操动机构运动控制系统中是一种行之有效的控制方法。

The operating mechanism of permanent magnet brushless DC motor for high voltage circuit breaker adopts a DC motor to drive the connecting rod of the circuit breaker to push the moving contact to complete the opening and closing operations.It has good fast response ability and control performance.In this paper,a simulation model of the brushless DC motor operating mechanism control system is constructed,and the fuzzy RBF neural network PID control algo-rithm and mathematical model are analyzed in detail.The traditional PID and fuzzy RBF neural network PID control strategies are used to simulate the control process of the moving contact motion characteristics of the high-voltage circuit breaker respectively.The results show that the fuzzy RBF neural network PID controller can better realize the speed tracking control of the moving contact,making it act according to the given movement speed characteristic curve,and realize the accurate control of the moving contact of the circuit breaker.It is proved that the fuzzy RBF neural network PID control strategy is an effective control method in the motion control system of the operating mechanism equipped with a brushless DC motor.