Master-slave synchronization for uncertain Markov jump neural networks with time-delay based on the sliding mode control

Wenjie You; Tianbo Wang; Wenjie You; Tianbo Wang

doi:10.3934/math.2024015

AIMS Mathematics

2024, Volume 9, Issue 1: 257-269. doi: 10.3934/math.2024015

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Research article

Master-slave synchronization for uncertain Markov jump neural networks with time-delay based on the sliding mode control

Wenjie You ,
Tianbo Wang ^,

School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai 201620, China

Received: 07 August 2023 Revised: 29 August 2023 Accepted: 12 September 2023 Published: 27 November 2023
MSC : 34D20

This paper investigated the master-slave synchronization for uncertain neural networks with time-delay by using the sliding mode control method. The uncertain parts in this neural network only needs to be bounded other than any structure condition. An integral sliding mode surface and sliding mode controller were designed such that the state trajectories of the neural networks could reach the sliding mode surface in finite time. Moreover, the computing method of the controller gain was proposed. Finally, a numerical example was provided to show the effectiveness of the obtained results.
- master-slave synchronization,
- neural network,
- Markovian jump,
- sliding mode control
Citation: Wenjie You, Tianbo Wang. Master-slave synchronization for uncertain Markov jump neural networks with time-delay based on the sliding mode control[J]. AIMS Mathematics, 2024, 9(1): 257-269. doi: 10.3934/math.2024015

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Abstract

This paper investigated the master-slave synchronization for uncertain neural networks with time-delay by using the sliding mode control method. The uncertain parts in this neural network only needs to be bounded other than any structure condition. An integral sliding mode surface and sliding mode controller were designed such that the state trajectories of the neural networks could reach the sliding mode surface in finite time. Moreover, the computing method of the controller gain was proposed. Finally, a numerical example was provided to show the effectiveness of the obtained results.

References

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