Robust adaptive control for a class of uncertain non-affine nonlinear systems using affine-type neural networks

Shitie Zhao and Xianwen Gao

International Journal of Systems Science, 2016, vol. 47, issue 11, 2691-2699

Abstract: A robust adaptive control is proposed for a class of single-input single-output non-affine nonlinear systems. In order to approximate the unknown nonlinear function, a novel affine-type neural network is used, and then to compensate the approximation error and external disturbance a robust control term is employed. By Lyapunov stability analysis for the closed-loop system, it is proved that tracking errors asymptotically converge to zero. Moreover, an observer is designed to estimate the system states because all the states may not be available for measurements. Furthermore, the adaptation laws of neural networks and the robust controller are given out based on the Lyapunov stability theory. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed control method.

Date: 2016
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DOI: 10.1080/00207721.2015.1015662

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