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Adaptive Neural Dynamic Compensator for Mobile Robots in Trajectory tracking control

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3 Author(s)
Rossomando, F.G. ; Gobierno de la Provincia de San Juan, San Juan, Argentina ; Soria, C. ; Carelli, R.

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.

Published in:

Latin America Transactions, IEEE (Revista IEEE America Latina)  (Volume:9 ,  Issue: 5 )