DocumentCode :
1697436
Title :
Self-tuning of PID parameters based on the modified particle swarm optimization
Author :
Huang, Guoming ; Wu, Dezhao ; Yang, Wailing ; Xue, Yuncan
Author_Institution :
Jiangsu Key Lab. of Power Transm. & Distrib. Equip. Technol., Hohai Univ., Changzhou, China
fYear :
2010
Firstpage :
5311
Lastpage :
5314
Abstract :
In this paper, a novel design method for determining the optimal proportional-integral-derivative (PID) controller parameters using the particle swarm optimization (PSO) algorithm is presented. This paper demonstrated in detail how to employ the PSO method to search efficiently the optimal PID controller parameters. To overcome premature of standard PSO algorithm, a modified PSO (MPSO) based on partial particle moving direction changing was proposed. It holds on the proprieties of simple structure, fast convergence, and at the same time, enhances the variety of the populations, extends the search space, and does not increase the computation complexity. Simulation results show that the algorithms are effective and the designed controller has excellent performance.
Keywords :
computational complexity; control system synthesis; particle swarm optimisation; self-adjusting systems; three-term control; MPSO; PID parameter self-tuning; computation complexity; controller design; modified PSO; modified particle swarm optimization; proportional-integral-derivative; search space; Algorithm design and analysis; Control systems; Convergence; Optimization; Particle swarm optimization; Search problems; Tuning; Genetic algorithm; Mutation; PID Controller; Particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
Type :
conf
DOI :
10.1109/WCICA.2010.5554822
Filename :
5554822
Link To Document :
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