Title: A backstepping controller based on RBFNN for mobile manipulator with unknown wheel slippage

Authors: Soni; Naveen Kumar

Addresses: Department of Mathematics, National Institute of Technology Kurukshetra, Haryana-136119, India ' Department of Mathematics, National Institute of Technology Kurukshetra, Haryana-136119, India

Abstract: In this paper, a backstepping-based control scheme for position tracking of a mobile manipulator in the presence of unknown wheel slippage, disturbances, and uncertainties is presented. The proposed control scheme takes the advantages of a backstepping controller because of its ability to handle uncertainties. Due to lack of prior knowledge regarding the dynamic characteristics of the mobile manipulator, smooth nonlinear dynamic functions are unknown, and for estimation a radial basis function neural network is used. The adaptive compensator is used at the kinematic and dynamic levels. At the kinematic level, the adaptive compensator diminishes the unwholesome effects of unknown wheel slips. At the dynamic level, the adaptive compensator supplies the influential robustness to vanquish the uncertainties because of external disturbances, reconstruction error, etc. The stability of the whole control system is validated with Lyapunov theory. The comparative simulation results are shown to confirm the efficiency and validity of the control scheme.

Keywords: RBF neural network; backstepping controller; adaptive compensator; unknown wheel slippage; mobile manipulator.

DOI: 10.1504/IJMIC.2024.136634

International Journal of Modelling, Identification and Control, 2024 Vol.44 No.2, pp.154 - 165

Received: 15 Sep 2022
Received in revised form: 23 Nov 2022
Accepted: 30 Nov 2022
Published online: 09 Feb 2024 *

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