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Adaptive Neuro-fuzzy Network Control for a Mobile Robot

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Abstract

A control structure that makes possible the integration of a kinematic controller and a neuro-fuzzy network (NFN) dynamic controller for mobile robots is presented. A combined kinematic/dynamic control law is developed using backstepping and stability is guaranteed by Lyapunov theory. The NFN controller proposed in this work can deal with unmodeled bounded disturbances and/or unstructured unmodeled dynamic in the mobile robot. On-line NFN parameter tuning algorithms do no require off-line learning yet guarantee small tracking errors and bounded control signals are utilized.

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Authors and Affiliations

  1. Department of Computer Control Engineering, Uiduk University, Kyongju, 780-713, South Korea

    Jun Oh Jang

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  1. Jun Oh Jang
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Correspondence to Jun Oh Jang.

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Jang, J.O. Adaptive Neuro-fuzzy Network Control for a Mobile Robot. J Intell Robot Syst 62, 567–586 (2011). https://doi.org/10.1007/s10846-010-9453-4

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  • DOI: https://doi.org/10.1007/s10846-010-9453-4

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