Fractional data-driven model for stabilization of uncertain discrete-time nonlinear systems

Abstract

This paper proposes a novel data-driven control for stabilization of a class of uncertain discrete-time nonlinear systems. The proposed method is based on the compact form dynamic linearization technique, which relates the first variation of the output signal with the fractional-order variation of the input one. Then, a discrete-time controller is proposed, based on the obtained fractional-order data-driven equivalent model. In order to compute the proposed controller and estimator, only input-output data information is considered. The uniform ultimately boundedness of the tracking errors are demonstrated by a formal analysis. Finally, comparison results based on simulations are presented to highlight the effectiveness of the proposed methodology.