Identification of time-varying delay systems using particle swarm optimization

Author

Ke, Jing ; Qiao, Yizheng ; Qian, Jixin

Author_Institution

Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China

Volume

1

fYear

2004

fDate

15-19 June 2004

Firstpage

330

Abstract

Particle swarm optimization algorithm is a new evolutionary computation method, which is applicable to complex optimization problems that are nonlinear, nondifferentiable and multimodal. A method for identification of time-varying delay systems using particle swarm optimization is proposed. The basic idea of the method is that the identification problems are cast as mixed-integer nonlinear programming problems, and then particle swarm optimization algorithm is used to find the optimal estimation of the time-varying parameters. Simulation results reveal that the suggested identification scheme possesses a good tracking ability to the time-varying delay systems.

Keywords

delay systems; evolutionary computation; integer programming; nonlinear programming; parameter estimation; time-varying systems; evolutionary computation method; identification method; mixed integer nonlinear programming problem; optimal parameter estimation; particle swarm optimization algorithm; time varying delay systems; time varying parameters; Computational modeling; Control systems; Delay systems; Evolutionary computation; Nonlinear control systems; Optimization methods; Parameter estimation; Particle swarm optimization; Systems engineering and theory; Time varying systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on

Print_ISBN

0-7803-8273-0

Type

conf

DOI

10.1109/WCICA.2004.1340586

Filename

1340586