Compensador neuronal dinámico adaptable para robots móviles en control de seguimiento de trayectorias (Adaptive Neural Dynamic Compensator for Mobile Robots in Trajectory tracking control)

Francisco Guido Rossomando (frosoma@inaut.unsj.edu.ar)


Univ. Nacional de San Juan
This paper appears in: Revista IEEE América Latina

Publication Date: Sept. 2011
Volume: 9,   Issue: 5 
ISSN: 1548-0992


Abstract:
In the present paper, it will be reported original results concerning the application of Neural Networks (NN) in mobile robot in trajectory tracking control. This work combines a feedback linearization based on a nominal model and an NN adaptive dynamic compensation. In mobile robot with uncertain dynamic parameters, two controllers are implemented separately: a kinematic controller and an inverse dynamic controller. The uncertainty in the nominal dynamic model is compensated by a neural adaptive feedback controller. The resulting adaptive controller is efficient and robust in the sense that it succeeds to achieve a good tracking performance with a small computational effort. The learning laws were deduced by Lyapunov's stability analysis. Finally, the performance of the control system is verified through experiments.

Index Terms:
adaptive inverse control, system identification,RBF neural nets, mobile robot control, Lyapunov theory   


Documents that cite this document
This function is not implemented yet.


[PDF Full-Text (612)]