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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 18/2021

10.03.2021 | Original Article

Sliding mode control-based fixed-time stabilization and synchronization of inertial neural networks with time-varying delays

verfasst von: Chaouki Aouiti, Qing Hui, Hediene Jallouli, Emmanuel Moulay

Erschienen in: Neural Computing and Applications | Ausgabe 18/2021

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Abstract

In this article, we are interested in the fixed-time stabilization (FTSt) and fixed-time synchronization (FTSy) of a class of inertial neural networks with time-varying and distributed delays. To obtain FTSt and FTSy, sliding mode controllers are developed based on sliding mode control techniques and by using sliding variables. Two polynomial feedback control laws are exploited to achieve the FTSt and the FTSy but they are singular. To get rid of the singularities, the saturation function is used into the design of the controllers and the almost FTSt and almost FTSy are proved. Finally, numerical examples are presented to show the effectiveness of the theoretical results.
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Metadaten
Titel
Sliding mode control-based fixed-time stabilization and synchronization of inertial neural networks with time-varying delays
verfasst von
Chaouki Aouiti
Qing Hui
Hediene Jallouli
Emmanuel Moulay
Publikationsdatum
10.03.2021
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 18/2021
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-021-05833-x

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