Francisco G. Rossomando, Carlos Soria, Eduardo O. Freire, and Ricardo O. Carelli
Adaptive neural control, nonlinear systems, mobile robot, sliding mode control.
It is well known that all robotic systems have additional dynamics and disturbances beyond those that are modelled. Hence, in this paper, the performance of a neuro-adaptive sliding mode control (NA-SMC) controller is analysed in the presence of disturbances and unmodelled dynamics. The proposed control strategy has two stages: first, a feedback linearization controller for a kinematic model; second, a neuro-adaptive SMC controller for a dynamic model. The entire control strategy is designed in discrete time using Lyapunov’s criterion, and the stability problems caused by direct implementation in discrete time to a system designed in a continuous domain are thereby avoided. The unmodelled dynamics introduce tracking errors in the closed-loop system; however, experiments made using the proposed approach to control mobile robots show that output tracking error tends to zero.
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