摘要
无刷直流电机存在的转矩脉动、速度不稳定等问题,是无刷直流电机需要解决的难点技术。提出了一种基于微粒群优化算法的模糊PID控制方法,将微粒群优化算法应用于模糊控制器的设计中,可以较好的实现电机速度的平稳以及具有较好的抑制负载扰动能力。在MATLAB上搭建了无刷直流电机和模糊PID控制器的仿真模型,对电机的启动、调速以及改变负载的运行情况进行了仿真。结果表明,上述系统具有更加理想的快速响应及稳定性效果,对系统参数和负载扰动变化都有较强的适应能力,采用微粒群优化算法的模糊PID控制的无刷直流电机速度输出更平稳,抗扰动能力更强。
In order to overcome the torque ripple and speed instability of BLDCM, this paper proposes a new control method based on self - adaptive fuzzy PID optimized by Particle Swarm Optimization Algorithm. The particle swarm optimization algorithm is applied to design the fuzzy controller, and the motor speed can be controlled smoothly and the load disturbance can be inhibited. The simulation model of a brushless DC motor with fuzzy PID controller through MATLAB is built, and the operation is simulated for motor starting as well as speed and load change. Simulation results show that the system has good performance with rapid response, ideal stability, strong robustness to the change of system parameters and load disturbances.
出处
《计算机仿真》
CSCD
北大核心
2015年第10期430-434,共5页
Computer Simulation
关键词
微粒群优化算法
模糊控制
无刷直流电机
Particle swarm optimization algorithm
Fuzzy controller
Brushless DC motor
