Adaptive Fuzzy Sliding Mode Controller with Predictive Control for Redundant Manipulators with Variable Payload

doi:10.16182/j.issn1004731x.joss.201803028

Abstract

Abstract: This paper presents an adaptive fuzzy sliding mode controller with Kalman predictive control (AFSMCK) for the redundant robotic manipulator handling a variable payload to achieve a precise trajectory tracking in the task space. This approach could be applied to solve the problems caused by the variable payload and model uncertainties. A Kalman predictive controller using the recursive algorithm is presented for an accurate prediction of a variable payload. The adaptive fuzzy logic algorithm is designed to approximate the parameters of the sliding mode controller to avoid chattering in real time. Lyapunov theory is applied to guarantee the stability of the proposed closed-loop robotic system. The effectiveness of the proposed control approach and theoretical discussion are proved by comparative simulation on a seven-link robot.

Key words: robot control, fuzzy logic, adaptive control, redundant manipulators, Kalman predictive control

CLC Number:

TP391.9

He Jun, Luo Minzhou, Zhao Jianghai, Xu Linsen, Li Tao. Adaptive Fuzzy Sliding Mode Controller with Predictive Control for Redundant Manipulators with Variable Payload[J]. Journal of System Simulation, 2018, 30(3): 994-1001.

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