ADAPTIVE-BACKSTEPPING POSITION CONTROL BASED ON RECURRENT-FWNNS FOR MOBILE MANIPULATOR ROBOT

Mai Thang Long

Abstract


In this paper, we proposed an adaptive-backstepping position control system for mobile manipulator robot (MMR). By applying recurrent fuzzy wavelet neural networks (RFWNNs) in the position-backstepping controller, the unknown-dynamics problems of the MMR control system are relaxed. In addition, an adaptive-robust compensator is proposed to eliminate uncertainties that consist of approximation errors and uncertain disturbances. The design of adaptive-online learning algorithms is obtained by using the Lyapunov stability theorem. The effectiveness of the proposed method is verified by comparative simulation results.


Keywords


backstepping controller, recurrent fuzzy wavelet, neural networks, adaptive robust control, mobile-manipulator robot.

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DOI: https://doi.org/10.15625/2525-2518/54/3A/11956 Display counter: Abstract : 68 views. PDF : 44 views.

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Published by Vietnam Academy of Science and Technology