State feedback controllers based finite-time and fixed-time stabilisation of high order BAM with reaction–diffusion term

Aouiti, Chaouki; Jallouli, Hediene

doi:10.1080/00207721.2020.1849861

Cited by 24 publications

(4 citation statements)

References 65 publications

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“…In recent years, there have been publications focusing on MINNs. For instance, the stability and existence of periodic solutions for delayed inertial BAM neural networks were studied [18]. In [19] , Wang and Zeng studied FTS problem of MINNs with distributed time delays.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, [22] focused on the fixed time synchronization of impulsive NNs using differential inequalities. Moreover, [30] explored the concepts of FTS and XTS for high-order BAM. These studies make significant contributions towards comprehending and applying XTS in various research and engineering domains [18] [29] [31].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, [30] explored the concepts of FTS and XTS for high-order BAM. These studies make significant contributions towards comprehending and applying XTS in various research and engineering domains [18] [29] [31].…”

Section: Introductionmentioning

confidence: 99%

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Fixed-Time Stabilization for a Class of Stochastic Memristive Inertial Neural Networks With Time-Varying Delays

Chen,

Zhang,

Chen

2024

IEEE Access

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This article investigates the fixed-time stabilization (XTS) of a class of stochastic memristive inertial neural networks (MINNs) with time-varying delays using interval matrix method (IMM) within the framework of the Filipov solution. To streamline the analysis, the second-order differential system is converted into an ordinary first-order differential system through suitable variable transformations. Afterwards, three types of state feedback controllers were designed. It's worth noting that the third controller represents an improvement over the first two controllers. Consequently, we have derived several sufficient conditions for XTS. This approach results in a more conservative upper estimate for the settling time function (STF). In addition, the finite-time stabilization (FTS) criterion can be derived. Ultimately, the validity of the theoretical findings were confirmed by numerical simulation outcomes.INDEX TERMS Feedback control, fixed-time stabilization, interval matrix method, inertial memristive neural networks.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fixed-Time Stabilization for a Class of Stochastic Memristive Inertial Neural Networks With Time-Varying Delays

Chen,

Zhang,

Chen

2024

IEEE Access

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“…The work [50] studied the stability of the RDSs with time delays by employing the LKF. The LKF was also used to solve the stabilization problems for RDSs with time-varying delays [1,6]. As a result, time delays are considered for RDSs [3,26,32,33,47,54].…”

Section: Introductionmentioning

confidence: 99%

Impulsive effects on stabilization of stochastic nonlinear reaction-diffusion systems with time delays and boundary feedback control

Gokulakrishnan¹,

Srinivasan²

2022

J. Math. Computer Sci.

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In this paper, we investigate the stabilization of stochastic nonlinear impulsive reaction-diffusion systems (SNIRDSs) with time delays and boundary feedback control via average impulsive interval approach. Boundary feedback control strategy are designed to stabilization of SNIRDSs. By constructing a Lyapunov-Krasovskii functional (LKF), and using Wirtinger's inequality, Gronwall inequality, average impulsive interval approach, sufficient conditions are derived to guarantee the finite-time stability (FTS) of proposed systems. We investigate the stabilization results by designing the control gain matrices for boundary feedback controller. The criterions are expressed in terms of linear matrix inequalities (LMIs) that can be verified by Matlab LMI toolbox. Finally, numerical example are given to verify the efficiency and superiority of proposed stabilization criterions.

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New feedback control techniques of quaternion fuzzy neural networks with time‐varying delay

Aouiti

Jallouli

2021

Intl J Robust & Nonlinear

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This article addresses the problems of fixed-time stabilization for a class of quaternion fuzzy neural networks (QFNNs) with time-varying delay. The QFNNs are developed by dividing our system into four real-valued parts based on the Hamilton rule. Then, based on fixed-time stability theory, some inequality techniques, and selecting the appropriate controllers and Lyapunov function, a novel criterion guaranteeing the fixed-time stabilization and the finite-time stabilization of the addressed system is derived. Finally, three numerical examples are presented to show the effectiveness of our theoretical results. K E Y W O R D S finite-time stabilization, fixed-time stabilization, fuzzy neural networks, quaternion neural networks, time-varying delay

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State feedback controllers based finite-time and fixed-time stabilisation of high order BAM with reaction–diffusion term

Cited by 24 publications

References 65 publications

Fixed-Time Stabilization for a Class of Stochastic Memristive Inertial Neural Networks With Time-Varying Delays

Fixed-Time Stabilization for a Class of Stochastic Memristive Inertial Neural Networks With Time-Varying Delays

Impulsive effects on stabilization of stochastic nonlinear reaction-diffusion systems with time delays and boundary feedback control

New feedback control techniques of quaternion fuzzy neural networks with time‐varying delay

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