Observer‐based finite‐time control of conformable Takagi–Sugeno fuzzy systems with time delay

ABSTRACT This paper examines finite‐time (F‐T) observer‐based control of fractional‐order nonlinear systems with time delay, employing the Takagi–Sugeno fuzzy (T‐SF) approach. This study utilizes the conformable fractional derivative (CFD) as its foundational framework. Sufficient conditions are formulated to guarantee that the augmented vector, consisting of the state estimates and the state estimation errors, stays within a ball centered at the origin. This applies not only to specified initial conditions but also to predefined disturbances. These conditions are then reformulated as linear matrix inequalities (LMIs) conditions, which can be efficiently solved using the LMI toolbox. An illustrative example is given to illustrate the proposed result.

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Publication Details

Journal
Asian Journal of Control
Published
2025-05-09
DOI
https://doi.org/10.1002/asjc.3692
Primary Topic
Chaos control and synchronization
Type
article
Field-Weighted Citation Impact
0.00
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article

Observer‐based finite‐time control of conformable Takagi–Sugeno fuzzy systems with time delay

Omar Kahouli, Zied Elleuch, Yassine Bouteraa, Ali Aloui et al.
Asian Journal of Control
Chaos control and synchronization
article

Observer‐based finite‐time control of conformable Takagi–Sugeno fuzzy systems with time delay

Omar Kahouli, Zied Elleuch, Yassine Bouteraa, Ali Aloui, Hamdi Gassara
article en

Abstract

ABSTRACT This paper examines finite‐time (F‐T) observer‐based control of fractional‐order nonlinear systems with time delay, employing the Takagi–Sugeno fuzzy (T‐SF) approach. This study utilizes the conformable fractional derivative (CFD) as its foundational framework. Sufficient conditions are formulated to guarantee that the augmented vector, consisting of the state estimates and the state estimation errors, stays within a ball centered at the origin. This applies not only to specified initial conditions but also to predefined disturbances. These conditions are then reformulated as linear matrix inequalities (LMIs) conditions, which can be efficiently solved using the LMI toolbox. An illustrative example is given to illustrate the proposed result.

Asian Journal of ControlVol. 28(1)
Prince Sattam Bin Abdulaziz University (SA), University of Sfax (TN), University of Ha'il (SA)
Openalex Percentile: Top 92%
Chaos control and synchronization
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