Journal of System Simulation
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.
Recommended Citation
Jun, He; Luo, Minzhou; Zhao, Jianghai; Xu, Linsen; and Tao, Li
(2019)
"Adaptive Fuzzy Sliding Mode Controller with Predictive Control for Redundant Manipulators with Variable Payload,"
Journal of System Simulation: Vol. 30:
Iss.
3, Article 28.
DOI: 10.16182/j.issn1004731x.joss.201803028
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol30/iss3/28
First Page
994
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201803028
Last Page
1001
CLC
TP391.9
Recommended Citation
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.
DOI
10.16182/j.issn1004731x.joss.201803028
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