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Adaptive dynamic programming methods in control of wheeled mobile robot

Hendzel Z., Szuster M.

International Journal of Applied Mechanics and Engineering

2012

Vol. 17, no. 3

837-851

The control problem of nonlinear systems is a demanding task that requires application of complex methods. The development of artificial intelligence methods in recent years has made it possible to design control systems able to adapt parameters to changing or unknown parameters of the controlled object or process. In the article, a new approach to the tracking control problem of a wheeled mobile robot is presented. It uses the newest methods of artificial intelligence, such as adaptive dynamic programming algorithms, in the tracking control task. The proposed tracking control system is compared to the neural control system and the PD controller in a problem of the mobile robot tracking control. Laboratory tests of the proposed control systems were advances performed using the wheeled mobile robot Pioneer 2-DX and the computational environment that makes real time control and data acquisition possible. The proposed tracking control systems are stable and do not require the stage of preliminary learning of neural networks.