Finite-time stability for fractional-order fuzzy neural network with mixed delays and inertial terms

Tiecheng Zhang; Liyan Wang; Yuan Zhang; Jiangtao Deng; Tiecheng Zhang; Liyan Wang; Yuan Zhang; Jiangtao Deng

doi:10.3934/math.2024935

AIMS Mathematics

2024, Volume 9, Issue 7: 19176-19194. doi: 10.3934/math.2024935

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Finite-time stability for fractional-order fuzzy neural network with mixed delays and inertial terms

1.
Huangshi Key Laboratory of Metaverse and Virtual Simulation, School of Mathematics and Statistics, Hubei Normal University, Huangshi, Hubei 435002, China
2.
School of Automation, Hubei University of Science and Technology, Xianning, Hubei 437100, China

Received: 15 April 2024 Revised: 24 May 2024 Accepted: 04 June 2024 Published: 07 June 2024
MSC : 93D09, 93D20, 93D23

This paper explored the finite-time stability (FTS) of fractional-order fuzzy inertial neural network with mixed delays. First, the dimension of the model was reduced by the order reduction method. Second, by leveraging the fractional-order finite-time stability theorem, fractional calculus and inequality methods, we established some sufficient conditions to guarantee the FTS of the model under feasible delay-dependent feedback controller and delay-dependent adaptive controller, respectively. Additionally, we derived the settling times (STs) for each control strategy. Finally, we provided two examples to substantiate our findings.
- finite-time stability,
- fractional-order,
- mixed delays,
- fuzzy,
- inertial neural network
Citation: Tiecheng Zhang, Liyan Wang, Yuan Zhang, Jiangtao Deng. Finite-time stability for fractional-order fuzzy neural network with mixed delays and inertial terms[J]. AIMS Mathematics, 2024, 9(7): 19176-19194. doi: 10.3934/math.2024935

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Abstract

This paper explored the finite-time stability (FTS) of fractional-order fuzzy inertial neural network with mixed delays. First, the dimension of the model was reduced by the order reduction method. Second, by leveraging the fractional-order finite-time stability theorem, fractional calculus and inequality methods, we established some sufficient conditions to guarantee the FTS of the model under feasible delay-dependent feedback controller and delay-dependent adaptive controller, respectively. Additionally, we derived the settling times (STs) for each control strategy. Finally, we provided two examples to substantiate our findings.

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