DocumentCode :
2764036
Title :
Fuzzy SVM Controller for Robotic Manipulator Based on GA and LS Algorithm
Author :
Zhu, Dequan ; Mei, Tao ; Luo, Minzhou ; Guan, Ke
Author_Institution :
Inst. of Intell. Machines, Chinese Acad. of Sci., Hefei, China
Volume :
6
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
263
Lastpage :
266
Abstract :
To improve the control precision of robotic manipulator, fuzzy support vector machines control method for robotic manipulator was presented based on genetic algorithm and least square algorithm. Fuzzy algorithm was used to decouple joints. Using support vector machines, fuzzy logical control of complete process and treatment of non-linear signal were realized. The controller parameters were optimized by hybrid learning algorithm. First, least square algorithm was used for off-line optimization to form support vector machines control system. Then, genetic algorithm was used for on-line optimization to get the optimal performance parameters of support vector machines and the optimal fuzzy proportional parameters. The simulation results of a two-link manipulator demonstrated that the control method designed gets tracking effect with high precision.
Keywords :
fuzzy control; genetic algorithms; learning systems; manipulators; support vector machines; fuzzy SVM controller; fuzzy logical control; genetic algorithm; hybrid learning algorithm; least square algorithm; online optimization; robotic manipulator; support vector machines; Control systems; Fuzzy control; Fuzzy logic; Genetic algorithms; Least squares methods; Manipulators; Process control; Robot control; Signal processing; Support vector machines; fuzzy control; genetic algorithm; least square algorithm; robotic manipulator; support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
Type :
conf
DOI :
10.1109/FSKD.2009.190
Filename :
5359842
Link To Document :
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