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Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots

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Abstract

In this work a neural indirect sliding mode control method for mobile robots is proposed. Due to the nonholonomic property and restricted mobility, the trajectory tracking of this system has been one of the research topics for the last ten years. The proposed control structure combines a feedback linearization model, based on a kinematics nominal model, and a practical design that combines an indirect neural adaptation technique with sliding mode control to compensate the dynamics of the robot. Using an online adaptation scheme, a neural sliding mode controller is used to approximate the equivalent control in the neighbourhood of the sliding manifold. A sliding control is appended to ensure that the neural sliding mode control can achieve a stable closed-loop system for the trajectory-tracking control of a mobile robot with unknown nonlinear dynamics. The proposed design simultaneously guarantees the stability of the adaptation of the neural nets and obtains suitable equivalent control when the parameters of the robot model are unknown in advance. The robust adaptive scheme is applied to a mobile robot and shown to be able to guarantee that the output tracking error will converge to zero.

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Authors and Affiliations

  1. Subsecretaría de Promoción Científica, Secretaría de de Estado de Ciencia, Tecnología e Innovación, Gobierno de San Juan, Centro Cívico Av. España 50 (S) Núcleo 3 5° Piso, CP J5400ARL, San Juan, Argentina

    Francisco G. Rossomando

  2. Instituto de Automática, Facultad de Ingeniería, Universidad Nacional de San Juan, Av. Libertador 1109 Oeste, 5400, San Juan, Argentina

    Carlos Soria & Ricardo Carelli

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  1. Francisco G. Rossomando
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  2. Carlos Soria
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  3. Ricardo Carelli
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Correspondence to Francisco G. Rossomando.

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Rossomando, F.G., Soria, C. & Carelli, R. Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots. J Intell Robot Syst 74, 931–944 (2014). https://doi.org/10.1007/s10846-013-9843-5

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  • DOI: https://doi.org/10.1007/s10846-013-9843-5

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