DocumentCode :
2555448
Title :
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
Link To Document :
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