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Force/position Control of Constrained Mobile Manipulators with Fast Terminal Sliding Mode Control and Neural Network

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Abstract

The purpose of this article is to present a fast terminal sliding mode control scheme for constrained mobile manipulators with both holonomic and non-holonomic constraints while taking uncertainties and external disturbances into account. Existing techniques cannot manage this kind of system because of the unavoidable errors in a mobile manipulator’s dynamical model. In order to improve position/force tracking performance of constrained mobile manipulators, a control scheme is presented that combines the advantages of fast terminal sliding mode control and neural networks. Without the requirement for offline training, the manipulator’s unknown dynamics are learned using a radial basis function neural network. Using an adaptive bound component, the bounds on uncertainties and neural network reconstruction error are quantified. The stability of the system and the convergence of the tracking errors are investigated using the Lyapunov theory. Analyzed simulation results indicate the proposed controller’s robust performance in a variety of circumstances.

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Authors and Affiliations

  1. Department of Mathematics, National Institute of Technology, Kurukshetra, Haryana, 136119, India

    Ruchika & Naveen Kumar

  2. Department of Applied Mathematics, Mahatma Jyotiba Phule Rohilkhand University, Bareilly, Uttar Pradesh, 243006, India

    Naveen Kumar

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  1. Ruchika
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Ruchika, Kumar, N. Force/position Control of Constrained Mobile Manipulators with Fast Terminal Sliding Mode Control and Neural Network. J Control Autom Electr Syst 34, 1145–1158 (2023). https://doi.org/10.1007/s40313-023-01032-2

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  • DOI: https://doi.org/10.1007/s40313-023-01032-2

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