Adaptive Neural Fault-Tolerant Control for Nonlinear Fractional-Order Systems with Positive Odd Rational Powers

In this paper, the problem of adaptive neural fault-tolerant control (FTC) for the fractional-order nonlinear systems (FNSs) with positive odd rational powers (PORPs) is considered. By using the radial basis function neural networks (RBF NNs), the unknown nonlinear functions from the controlled syst...

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Bibliographic Details
Main Authors: Jiawei Ma, Huanqing Wang, Yakun Su, Cungen Liu, Ming Chen
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Fractal and Fractional
Subjects:
Online Access:https://www.mdpi.com/2504-3110/6/11/622
Description
Summary:In this paper, the problem of adaptive neural fault-tolerant control (FTC) for the fractional-order nonlinear systems (FNSs) with positive odd rational powers (PORPs) is considered. By using the radial basis function neural networks (RBF NNs), the unknown nonlinear functions from the controlled system can be approximated. With the help of an adaptive control ideology, the unknown control rate of the actuator fault can be handled. In particular, the FNSs subject to high-order terms are studied for the first time. In addition, the designed controller can ensure the boundedness of all the signals of the closed-loop control system, and the tracking error can tend to a small neighborhood of zero in the end. Finally, the illustrative examples are shown to validate the effectiveness of the developed method.
ISSN:2504-3110