Exponential state estimation for delayed competitive neural network via stochastic sampled-data control with Markov jump parameters under actuator failure

• Autorzy: Cao Yang , Subhashri Alwarappan Ravisankar , Chandrasekar A. , Radhika T. , Przybyszewski Krzysztof

Identyfikatory

DOI

10.2478/jaiscr-2024-0020

• Języki publikacji: EN

Abstrakty

EN

This article examines the problem of estimating the states of Markovian jumping competitive neural networks, where the estimation is done using stochastic sampled-data control with time-varying delay. Instead of continuously measuring the states, the network relies on sampled measurements, and a sampled-data estimator is proposed. The estimator uses probabilistic sampling during two sampling periods, following a Bernoulli distribution. The article also takes into account the possibility of actuator failure in real systems. To ensure the exponentially mean-square stability of the delayed neural networks, the article constructs a Lyapunov-Krasovskii functional (LKF) that includes information about the bounds of the delay. The sufficient conditions for stability are derived in the form of linear matrix inequalities (LMIs) by employing modified free matrix-based integral inequalities. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.

Słowa kluczowe

EN

stochastic sampled-data control; competitive neural networks; state estimation; Markov jump; actuator failure

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2024
• Tom: Vol. 14, No. 4
• Strony: 373--385
• Opis fizyczny: Bibliogr. 18 poz., rys.

Twórcy

autor

Cao Yang

• School of Cyber Science and Engineering, Southeast University, Nanjing 211189, China

• https://orcid.org/0000-0002-6940-0868

autor

Subhashri Alwarappan Ravisankar

• Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore-632 014, Tamilnadu, India

• https://orcid.org/0009-0008-7514-3360

autor

Chandrasekar A.

• Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore-632 014, Tamilnadu, India

• https://orcid.org/0000-0003-0883-8863

autor

Radhika T.

• Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore-632 014, Tamilnadu, India

• https://orcid.org/0000-0003-2908-4618

autor

Przybyszewski Krzysztof

• Institute of Information Technologies, University of Social Sciences, ul. Sienkiewicza 9, 90-113 Łodź, Poland

• https://orcid.org/0000-0002-7694-365X

Bibliografia

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• [15] G. Zhang, J. Zhang, W. Li, C. Ge, Y. Liu, Exponential synchronization of delayed neural networks with actuator failure using stochastic sampled-data control, International Journal of Control, Automation and Systems, 20 (2022) 691–701.
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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).