Control neuro-robusto del sistema líder-seguidor de agentes móviles

David  Rodriguez-Castellanos; Gualberto  Solis-Perales; Marco Blas-Valdez

doi:10.29057/icbi.v10iEspecial5.10131

Authors

David Rodriguez-Castellanos Universidad de Guadalajara https://orcid.org/0000-0003-3526-4121
Gualberto Solis-Perales Universidad de Guadalajara https://orcid.org/0000-0003-4472-8717
Marco Blas-Valdez Universidad de Guadalajara https://orcid.org/0000-0002-7956-6044

DOI:

https://doi.org/10.29057/icbi.v10iEspecial5.10131

Keywords:

Recurrent High-Order Neural Networks (RHONN), Differential-Drive Mobile Robot, Asymptotic Output Tracking, Neuro-Robust Control

Abstract

In this work applying output feedback linearization, a neuro-robust controller based on a recurrent high-order neural network is proposed, applied to differential drive mobile robot tracking. The tracking is done on the the wheels angular velocities. The strategy consists in desing a linearizing controller and an estimator based on neural networks for the parametric uncertainties and possible discrepancies in the model. In this way only angular velocities are required as output variables. A numerical simulation is presented to illustrate the proposal.

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Publisher: Universidad Autónoma del Estado de Hidalgo

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