无刷电机粒子群PID算法的优化研究

作者：任,徐晓柏 日期：2008-12-26/span> 浏览：3811 查看PDF文档

无刷电机粒子群PID算法的优化研究

任,徐晓柏
（杭州电子科技大学 软件与智能技术研究所，浙江 杭州 310018）

摘要：针对无刷电机这样一个复杂的、耦合的非线性对象，传统的一些控制算法存在许多缺点，例如速度精度控制不够、响应速度慢等，其主要原因是对PID控制器的系数整定没有一个更合理的方法。在充分考虑了无刷电机的这种机械特性的基础上，提出了一种改进的粒子群算法，对PID系数进行了整定，并采用了线性方法调准速度权值，采用反余弦函数构造加速因子的调整策略。Matlab/Simulink仿真结果证明，此算法具有较好的快速性、稳定性和鲁棒性。
关键词：粒子群;个体极值;全局极值;无刷电机;鲁棒性
中图分类号：TP273文献标识码：A文章编号：1001-4551(2008)11-0065-03

Optimization research of PSO-PID algorithm for the brushless DC motor
REN Yu, XV Xiao-bai
(Institute of Software and Computer Intelligent Control, Hangzhou Dianzi University, Hangzhou 310018, China)
Abstract: Aiming at a complicated coupling and non-linear brushless DC motor(BLDCM) servo system, the conventional algorithms have many disadvantages, such as less precision, lower speed response. The main reason is that it has not a good way to tuning the coefficient of PID. Taking the mechanical characteristics of BLDCM into consideration, an improved particle swarm optimization(PSO) algorithm was presented to tune the coefficient of PID. The linear method was adopted to alignment inertial constant, and the anti-cosine function was adopted to adjust the learning factor. The Matlab/Simulink simulation results show that the algorithm has a good fast, stability, and robustness.
Key words: particle swarm optimization(PSO); personal best; group best; brushless DC motor(BLDCM); robustness