基于粒子群优化算法的主动磁悬浮PID控制器研究

Zhang Yanhong, Zheng Zhong-qiao, Zhang Jiansheng, Yinjie Lei
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引用次数: 4

摘要

主动磁悬浮控制系统是一个开环的不稳定控制系统。PID控制器的参数通常是根据设计者的经验来设定的。它不仅费时、繁琐,而且不能精确控制。因此本文采用粒子群优化算法,结合PID控制器对PID控制器的参数进行优化。采用PID控制器的比例系数、积分系数和微分系数作为粒子群优化算法的三个粒子。选择准确的初始化参数,更新速度和位置信息,实现粒子的全局优化。因此,得到了PID控制器的三个优化参数,并将其用于磁悬浮主动控制系统的仿真。仿真结果表明,优化后的参数能使主动磁悬浮控制系统稳定运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on PID Controller in Active Magnetic Levitation Based onParticle Swarm Optimization Algorithm
Active magnetic levitation control system is an open-loop and unstable control system. The parameters of PID controller are usually set according to the experience of the designer. It is not only time-consuming and tedious, but also can’t be controlled accurately. So the particle swarm optimization algorithm is used in this paper, which is used to optimize the parameters of PID controller by combining with PID controller. The proportional coefficient, integral coefficient and differential coefficient of PID controller are used as three particles of the particle swarm optimization algorithm. The accurate initialization parameters are selected, and then the speed and position information is updated to realize the global optimization of particle. Therefore, the three optimized parameters of PID controller are obtained, which are used to simulate the active magnetic levitation control system. The simulation result shows that the optimized parameters can make the active magnetic levitation control system stable.
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