Adaptive Control for Fractional-order Interconnected Systems

This paper focuses on a class of fractional-order interconnected system. A decentralized adaptive controller is designed based on the fractional Lyapunov direct method. In order to solve the interactions between subsystems, a compensation term is presented. In addition, the various uncertainties, such as unknown parameters, disturbances and nonlinear functions, are considered and estimated by the proposed fractional-order update laws. Especially, neural networks are adopted to approximate the unknown nonlinear functions. Furthermore, a fractional-order auxiliary system is constructed to deal with the input nonlinearities with backlash and saturation. Finally, the effectiveness of the proposed control scheme is verified by some simulation examples.

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