摘要
针对传统的无刷直流电机控制无法在线调整参数、难以精确控制的问题,提出一种基于改进的粒子群优化(PSO)算法的模糊PID控制器设计。通过对粒子群优化算法的参数进行分时段更新,实现模糊PID控制器参数动态全局优化,来确定使用双闭环控制模型的无刷直流电机的最优参数。Matlab仿真结果表明,该研究方法较传统方法可使得转速无超调、减少调节时间,同时启动时转矩脉动较小。
An improved particle swarm optimization （PSO） algorithm is put forward for the precise control of Brushless DC Motor by adjusting the parameters online. The updated parameters of particle swarm optimization （tx30） algorithm is used to dynamically optimize the parameters of the fuzzy PID controller, which determines the op- timal parameters of double closed loop control model of the Brushless DC Motor. The simulated results of Matlab show that the method effectively decreases the adjusting time without overshoot of speed with smaller starting torque ripple.
出处
《电子科技》
2016年第9期37-40,共4页
Electronic Science and Technology
