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Joint friction identification for robots using TSK fuzzy system based on subtractive clustering

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5 Author(s)
Zhongkai Qin ; Dept. of Mech. Eng., Ecole Polytech. de Montreal, Montreal, QC ; Qun Ren ; Baron, L. ; Balazinski, M.
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In this paper, the joint friction of a robotic manipulatoris identified by using subtractive clustering based Takagi-Sugeno-Kang (TSK) fuzzy logic system (FLS). The proposed approach can provide accurate prediction of the joint friction despite the nonlinearity of the friction and measurement uncertainty. Simulation results show the effectiveness and convenience of the method.

Published in:

Fuzzy Information Processing Society, 2008. NAFIPS 2008. Annual Meeting of the North American

Date of Conference:

19-22 May 2008