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In this paper, a decentralized adaptive neural network sliding mode control scheme is proposed for trajectory tracking control problem of reconfigurable manipulators based on data-based modeling. This method can be implemented to reconfigurable manipulators with different configurations and degrees of freedom without modifying any control parameters. Different from the previous works, the proposed...
This paper addresses the problems of trajectory tracking control of a reconfigurable manipulator with harmonic drive transmission under a decentralized integral sliding mode control method, and a high-performance control is achieved based on adaptive super-twisting algorithm. First, the dynamic model of the reconfigurable manipulator is formulated with a nonlinear harmonic drive model. Second, based...
This paper presents a novel position/force control approach for a constrained reconfigurable manipulators. First, the reduced-order dynamic model of the constrained reconfigurable manipulator system is formulated. Second, a sliding mode control method with adaptive neural network is proposed with guaranteed control performance. The neural network system is used to estimate the nonlinear parts that...
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