Adaptive fuzzy command filtered control for uncertain fractional order nonlinear systems with full state constraints

This paper investigates the tracking control problem for fractional-order (FO) nonlinear systems with model uncertainties and external disturbances under full-state constraints. An adaptive fuzzy control strategy based on a command filter is proposed, where the asymmetric Barrier Lyapunov Function is adopted to ensure that the states do not violate their constraints, and a fuzzy logic system is used to approximate the unknown nonlinear terms. Additionally, a FO command filter is implemented to approximate the virtual control signals and their derivatives, effectively addressing the explosion of complexity problem, while an error compensation function is incorporated to compensate for the filtering errors. Overall, the stability analysis is conducted based on the Lyapunov method to ensure the boundedness of all signals. Ultimately, the performance of the proposed controller is demonstrated through two simulation examples.

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Publication Details

Journal
Scientific Reports
Published
2025-02-07
DOI
https://doi.org/10.1038/s41598-025-88784-w
Citations
8
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
9.72
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article

Adaptive fuzzy command filtered control for uncertain fractional order nonlinear systems with full state constraints

Ruixia Liu, Liyang Sun, Lei Xing, Yang Han
8 citations
Scientific Reports
Adaptive Control of Nonlinear Systems
9.72
article

Adaptive fuzzy command filtered control for uncertain fractional order nonlinear systems with full state constraints

Ruixia Liu, Liyang Sun, Lei Xing, Yang Han
article en
8 citations

Abstract

This paper investigates the tracking control problem for fractional-order (FO) nonlinear systems with model uncertainties and external disturbances under full-state constraints. An adaptive fuzzy control strategy based on a command filter is proposed, where the asymmetric Barrier Lyapunov Function is adopted to ensure that the states do not violate their constraints, and a fuzzy logic system is used to approximate the unknown nonlinear terms. Additionally, a FO command filter is implemented to approximate the virtual control signals and their derivatives, effectively addressing the explosion of complexity problem, while an error compensation function is incorporated to compensate for the filtering errors. Overall, the stability analysis is conducted based on the Lyapunov method to ensure the boundedness of all signals. Ultimately, the performance of the proposed controller is demonstrated through two simulation examples.

Scientific ReportsVol. 15(1)
Harbin Institute of Technology (CN), Xi’an University of Posts and Telecommunications (CN), Northeast Petroleum University (CN)
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Openalex Percentile: Top 2%
Adaptive Control of Nonlinear Systems
9.72
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