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Erschienen in: Neural Computing and Applications 7/2024

06.12.2023 | Original Article

Finite-time adaptive fuzzy control of nonlinear systems with actuator faults and input saturation

verfasst von: Jiafeng Li, Ruihang Ji, Xiaoling Liang, Hao Yan, Shuzhi Sam Ge

Erschienen in: Neural Computing and Applications | Ausgabe 7/2024

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Abstract

This paper addresses the finite-time control problem of a class of uncertain nonlinear systems subject to input saturation and actuator faults. To approximate the unknown system states, a fuzzy state observer is established where fuzzy logic systems are utilized to estimate the unknown nonlinearities. A nonlinear disturbance observer to estimate the external disturbance of the system. A new finite-time adaptive fuzzy controller is constructed together with the proposed disturbance and state observers, which can guarantee the tracking error into a small neighborhood around zero within finite time. To avoid the tedious and arithmetic problems brought by the traditional backstepping control, the dynamic surface technique is applied, which can effectively reduce the computation burden. It can be proved that not only the boundedness of the closed-loop system states can be guaranteed but also the tracking error is regulated into a small range near the equilibrium in finite time, despite unknown actuator faults and input saturation. Finally, the simulations of two-stage chemical reactor nonlinear system are conducted to demonstrate the effectiveness of the proposed method.

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Metadaten
Titel
Finite-time adaptive fuzzy control of nonlinear systems with actuator faults and input saturation
verfasst von
Jiafeng Li
Ruihang Ji
Xiaoling Liang
Hao Yan
Shuzhi Sam Ge
Publikationsdatum
06.12.2023
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 7/2024
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-023-09222-4

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