Fuzzy Support Vector Machines Control for Robotic Manipulator

De Quan Zhu; Tao Mei; Cheng Mao Cao

doi:10.4028/www.scientific.net/AMR.204-210.301

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 204-210Fuzzy Support Vector Machines Control for Robotic...

Fuzzy Support Vector Machines Control for Robotic Manipulator

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 parameters of controller 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. Simulation results of a two-link manipulator demonstrated that the control method designed gets tracking effect with high precision.

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Periodical:

Advanced Materials Research (Volumes 204-210)

Pages:

301-305

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.204-210.301

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Online since:

February 2011

Authors:

De Quan Zhu, Tao Mei, Cheng Mao Cao

Keywords:

Fuzzy Control, Genetic Algorithm (GA), Least Square Algorithm, Robotic Manipulator, Support Vector Machine (SVM)

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