Decentralized adaptive neural network sliding mode position/force control of constrained reconfigurable manipulators

A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to s...

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Veröffentlicht in:	Journal of Central South University 2016-11, Vol.23 (11), p.2917-2925
1. Verfasser:	李元春丁贵彬赵博
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive control Closed loops Constraints Contact force Control Science and Information Engineering Decentralized control Engineering Feedback control Jacobi matrix method Jacobian matrix Manipulators Mechanical Engineering Metallic Materials Neural networks Reconfiguration Robot arms Sliding mode control Stability Subsystems
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