摘要
针对常规粒子群优化算法存在的鲁棒性能差的问题,提出一种基于多模型的粒子群优化方法.将其应用于对PID控制器参数的优化,有效地避免了PID控制器设计中复杂的参数调试.即使在模型失配的情况下,控制系统仍保持了良好的控制品质和鲁棒性.通过对几个典型被控对象的仿真实验,证明了所提出的优化算法的实用性、有效性和优越性.*
A particle swarm optimization （PSO） algorithm based on multi-model is proposed to overcome the problem of poor robustness in general PSO algorithm. The algorithm is applied to optimize the control parameters of PID and the complex adjustment of parameters in PID controller design is effectively avoided. Even in the case of model mismatch, the control system can maintain better control performance and have stronger robustness. Simulation experiments have been made on several typical controlled objects to demonstrate the practicality, effectiveness and superiority of the proposed optimization algorithm.
出处
《信息与控制》
CSCD
北大核心
2006年第6期711-714,720,共5页
Information and Control
关键词
PID控制
参数优化
粒子群优化
多目标
鲁棒性
PID control
parameter optimization
particle swarm optimization
muhiple objective
robustness
