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    Control of a robotics wheelchair using recurrent networks

    TitleControl of a robotics wheelchair using recurrent networks
    Publication TypeJournal Article
    Año de publicación2005
    AutoresBoquete, L, Barea Navarro, R, Garcia, R, Mazo, M, Sotelo, MA
    Idioma de publicaciónEnglish
    JournalAutonomous Robots
    Volumen18
    Número1
    Páginas5-20
    Fecha de publicación01/2005
    Lugar de publicaciónNetherlands
    EditorialSpringer Netherlands
    Rank in category2/11
    JCR CategoryROBOTICS
    Palabras claveadaptive control, dynamics, identification, neurocontrol, radial basis function, recurrent neural networks, stability
    JCR Impact Factor1.246
    ISSN0929-5593
    URLhttp://www.springerlink.com/content/r9k255l110j7w855/
    DOI10.1023/B:AURO.0000047285.40228.eb
    Abstract

    This paper describes an adaptive neural control system for governing the movements of a robotic wheelchair. It presents a new model of recurrent neural network based on a RBF architecture and combining in its architecture local recurrence and synaptic connections with FIR filters. This model is used in two different control architectures to command the movements of a robotic wheelchair. The training equations and the stability conditions of the control system are obtained. Practical tests show that the results achieved using the proposed method are better than those obtained using PID controllers or other recurrent neural networks models

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