摘要
提出了一种基于GA s/PSO组合算法的P ID控制器参数自整定方法,这种方法兼有遗传算法(GA s)和粒子群算法(PSO)的优点。组合算法种群由GA s和PSO的最佳个体迁移形成,其中GA s采用了实数编码和变异概率自适应,PSO算法采用了带指数衰减的惯性因子的速度更新算法,以加快收敛速度。通过对水轮机调速系统P ID控制器参数寻优仿真比较表明,该组合算法寻优性能比单独的GA s和PSO表现更为优异,且所得系统具有更好的动态性能。
A PID controller parameter auto-tuning approach based on GAs/PSO combination algorithm is proposed, which has the advantages of genetic algorithm （GAs） and particle swarm optimization （PSO）. The new population of combination algorithm is formed by immigration of best GA and PSO individuals, in which the real coding and adaptive mutation factor are employed in GA and the exponentially degeneration momentum factor is adopted in velocity updating of PSO, which can speed up the convergence of PSO. The simulation results in PID parameter optimization of hydraulic turbine speed regulating system show that the combination algorithm is superior to the single GAs or PSO one, the dynamic performance of closed loop system is satisfactory.
出处
《华东理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第7期893-896,共4页
Journal of East China University of Science and Technology
基金
国家自然科学基金(60274020)
博士点基金(20050487013)
