Title :
Evolutionary algorithms based parameters tuning of PID controller
Author :
Junli, Li ; Jianlin, Mao ; Guanghui, Zhang
Author_Institution :
Coll. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
Abstract :
In this paper, performance comparison of evolutionary algorithms (EAs) such as real coded genetic algorithm (RGA), standard partical swarm optimization (SPSO), modified particle swarm optimization (MPSO), Niche particle swarm Algorithm (NPSA) on optimal design of PID controller is considered. EAs simulations are carried with minimization of ITAE as objective using one types of stopping criteria, namely, terminate iteration. Results clearly indicate the better performance of SPSO and MPSO designed PID controller on SISO system.
Keywords :
control system synthesis; genetic algorithms; particle swarm optimisation; Niche particle swarm algorithm; PID controller; SISO system; evolutionary algorithms; modified particle swarm optimization; optimal design; parameters tuning; real coded genetic algorithm; standard partical swarm optimization; Algorithm design and analysis; Computers; Genetic algorithms; Optimization; Particle swarm optimization; Tuning; Evolutionary algorithm; PID Control; Parameter tuning; optimization;
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
DOI :
10.1109/CCDC.2011.5968215
