DocumentCode
1657586
Title
PSO-based Parameter Estimation of Nonlinear Systems
Author
Meiying, Ye ; Xiaodong, Wang
Author_Institution
Zhejiang Normal Univ., Jinhua
fYear
2007
Firstpage
533
Lastpage
536
Abstract
A technique based on particle swarm optimization is proposed for improving the accuracy of parameter estimation of nonlinear systems. The effectiveness of the particle swarm optimization algorithms is compared with different genetic algorithms in terms of parameter accuracy. Simulation results of two kinds of process systems will be illustrated to show that the more accurate estimation of unknown system parameters can be achieved by using the proposed technique.
Keywords
genetic algorithms; nonlinear control systems; parameter estimation; particle swarm optimisation; PSO; genetic algorithms; nonlinear systems; parameter accuracy; parameter estimation; particle swarm optimization; Control engineering; Control systems; Degradation; Genetic algorithms; Nonlinear control systems; Nonlinear systems; Parameter estimation; Particle swarm optimization; Physics; System identification; Nonlinear Systems; Parameter Estimation; Particle Swarm Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference, 2007. CCC 2007. Chinese
Conference_Location
Hunan
Print_ISBN
978-7-81124-055-9
Electronic_ISBN
978-7-900719-22-5
Type
conf
DOI
10.1109/CHICC.2006.4347606
Filename
4347606
Link To Document