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

Authors

  • Mai Thang Long Faculty of Electronics Technology, Industrial University of HCMC, 12 Nguyen Van Bao, Go Vap, Hochiminh

DOI:

https://doi.org/10.15625/2525-2518/54/3A/11956

Keywords:

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

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.

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Published

2018-03-20

Issue

Section

Articles