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

In this paper, the joint friction of a robotic manipulator is 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.