摘要
应用改进的思维进化算法优化PID参数。思维进化算法的子群体间彼此独立操作,因此会有重复操作,重叠的区域,因而造成资源浪费。将小生境技术引入到思维进化算法。它对群体进行划分,减少重复搜索,保持群体的多样性,提高搜索效率。通过对具有严重参数不确定性、多扰动以及大迟延的电厂主汽温被控对象的仿真研究,结果表明:改进的思维进化算法寻优速度快,计算量小,对PID参数优化是非常有效的,使得主汽温控制系统取得了较好的控制品质,系统的鲁棒性比较强。
The improved mind evolutionary algorithm （MEA） was used to optimize the PID controller parameters. According to the defects lying in mind evolutionary algorithm, the niche technique is developed to improve MEA in this paper. The swarm is classified and reduced the searching zone, which keeps the swarm diversity and to speed up optimization. According to the delay phenomena that may appear in the particle swarm algorithm, the reboot strategy is introduced. The controlling of main steam temperature in power plant is studied. The simulation results show that the improved MEA is very effective.
出处
《华北电力大学学报（自然科学版）》
CAS
北大核心
2008年第1期37-40,共4页
Journal of North China Electric Power University：Natural Science Edition
关键词
思维进化算法
PID控制
小生境
主汽温
mind evolutionary algorithm
PID control
niche
main steam temperature
