Sliding mode control based on particle swarm optimization and support vector machine

Author

Liu, Mingdan ; Chen, Zhimei ; Sun, Zhebin

Author_Institution

Sch. of Electron. & Inf. Eng., Taiyuan Univ. of Sci. & Technol., Taiyuan, China

fYear

2011

fDate

21-25 June 2011

Firstpage

260

Lastpage

264

Abstract

In this paper, a new method of sliding mode control (SMC) is proposed for a class of discrete-time system based on particle swarm optimization (PSO) and support vector machine (SVM). Parameters, which were limited by determining previously in the conventional reaching law, are adjusted by PSO and SVM on line. The tracking speed of the control system is accelerated according to this method. The disadvantages of large calculation and low precision of SVM are overcome by the method of combination to the PSO. And quality of control system is improved and the system chattering is weakened through the method. Simulation results show the effectiveness of it.

Keywords

discrete time systems; particle swarm optimisation; support vector machines; variable structure systems; discrete-time system; particle swarm optimization; sliding mode control; support vector machine; Artificial neural networks; Genetic algorithms; Particle swarm optimization; Sliding mode control; Sun; Support vector machines; particle swarm optimization; sliding mode control; support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2011 9th World Congress on

Conference_Location

Taipei

Print_ISBN

978-1-61284-698-9

Type

conf

DOI

10.1109/WCICA.2011.5970739

Filename

5970739