DocumentCode
2511493
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
fYear
2011
fDate
23-25 May 2011
Firstpage
416
Lastpage
420
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location
Mianyang
Print_ISBN
978-1-4244-8737-0
Type
conf
DOI
10.1109/CCDC.2011.5968215
Filename
5968215
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