基于改进粒子群算法的大迟延热工对象PID参数优化  

Optimization of PID Parameters for Large Delay Thermal Engineering Objects Based on Improved Particle Swarm Optimization

作　　者：马鑫泰 何同祥[1] Ma Xintai;He Tongxiang(School of Control and Computer Engineering,North China Electric Power University,Hebei,Baoding,071003,China)

机构地区：[1]华北电力大学控制与计算机工程学院,河北保定071003

出　　处：《仪器仪表用户》2019年第3期87-89,共3页Instrumentation

摘　　要：对粒子群算法进行改进,并应用于大迟延热工对象,对PID控制器参数进行优化。本算法加快了粒子群算法的收敛速度,提高了寻优能力。将改进的粒子群算法和标准粒子群算法进行比较,结果表明:利用改进粒子群算法整定的PID参数,减小了超调量,同时缩减了调节时间。The particle swarm optimization algorithm is improved and applied to large delay thermal objects to optimize PID controller parameters.The algorithm accelerates the convergence speed of the particle swarm optimization algorithm and improves the optimization ability.Comparing the improved particle swarm optimization algorithm with the standard particle swarm optimization algorithm,the results show that the PID parameters adjusted by the improved particle swarm optimization algorithm reduce the overshoot and reduce the adjustment time.

关 键 词：粒子群算法 PID控制 算法改进 参数优化 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置]