磁浮系统中免疫专家PID控制器的改进

磁浮系统是一种典型的非线性、不稳定性开环系统。由于传统的比例-积分-微分（PID）控制器的参数是固定的,因此,控制系统无法兼顾悬浮系统的静态和动态性能。本文提出一种基于粒子群优化（PSO）算法的分段专家免疫PID控制器。该控制器先利用免疫PID控制器给出悬浮系统的阶跃响应曲线,再根据误差变化将该曲线划分为五个阶段,分段实现基于PSO算法的专家PID控制器。该控制器的优点是能够在悬浮系统工作时在线对PID参数进行调节,适应误差的不同变化,使控制器响应速度加快、调节精度提高,稳态性能变好,而且几乎没有超调和振荡。利用Matlab仿真,结果表明在相同精度要求下,该控制方法与单一的专家PID控制器的相比,磁浮控制系统的过渡时间变短,调节时间变短且过渡性能较好。

Improvement of Immune Expert PID Controller in Magnetic Suspension System

Magnetic suspension system（MSS） is characterized by its nonlinear and instability. Since the parameters of the traditional proportional-integral-differential（PID） controller＆amp;nbsp;is fixed, the control system is unable to satisfy the static and dynamic performances of a magnetic suspension system. In this article, a piecewise-expert-immune（PID）controller based on the particle swarm optimization algorithm （PIEPID-PSO） was proposed. The controller first used immune PID controller to make the step response curve of a MSS, then the curve was divided into five stages according to the different changes of error, and the MSS was controlled with the expert PID control strategy on the basis of the particle swarm optimization by the stages. The advantages of the controller in a MSS are capable to adjust PID parameters to adapt different changes of error online, and to have fast response speed, high adjustment precision, good steady state performance, and almost without overshoot and oscillation. Simulating with MATLAB, the simulation result showed that in the same precision requirement, and compared with the single expert PID controller, the new control system was shorter in adjusting time, smaller in overshoot and better in transient performance for a MSS.