Regular Papers

International Journal of Control, Automation, and Systems 2023; 21(9): 2927-2937

https://doi.org/10.1007/s12555-022-0452-6

© The International Journal of Control, Automation, and Systems

Dynamic Event-triggered Exponential Synchronization for Neural Networks With Random Controller Gain Perturbations

Chao Ge*, Chenlei Chang, Yajuan Liu, and Changchun Hua

North China University of Science and Technology

Abstract

The exponential synchronization for a class of neural networks (NNs) based on dynamic event-triggered mechanism (DETM) is researched in this article. Firstly, an unbounded distributed delay is introduced into the NNs. Next, based on the characteristics of the sawtooth structure, an improved bilateral Lyapunov-Krasovskii functional (LKF) is constructed, which involves more information. By using improved integral inequality, some sufficient conditions are achieved for the exponential stability of the synchronization error system. Due to the influence of external factors or internal components, the controller parameter is uncertain. Then, a non-fragile controller is designed based on the decoupling technique. Moreover, a co-design scheme of controller gain and event-triggered matrix is obtained based on the linear matrix inequality technique. Finally, two examples are used to illustrate the validity and feasibility of the presented method.

Keywords Dynamic event-triggered mechanism, exponential synchronization, neural networks, non-fragile controller.

Article

Regular Papers

International Journal of Control, Automation, and Systems 2023; 21(9): 2927-2937

Published online September 1, 2023 https://doi.org/10.1007/s12555-022-0452-6

Copyright © The International Journal of Control, Automation, and Systems.

Dynamic Event-triggered Exponential Synchronization for Neural Networks With Random Controller Gain Perturbations

Chao Ge*, Chenlei Chang, Yajuan Liu, and Changchun Hua

North China University of Science and Technology

Abstract

The exponential synchronization for a class of neural networks (NNs) based on dynamic event-triggered mechanism (DETM) is researched in this article. Firstly, an unbounded distributed delay is introduced into the NNs. Next, based on the characteristics of the sawtooth structure, an improved bilateral Lyapunov-Krasovskii functional (LKF) is constructed, which involves more information. By using improved integral inequality, some sufficient conditions are achieved for the exponential stability of the synchronization error system. Due to the influence of external factors or internal components, the controller parameter is uncertain. Then, a non-fragile controller is designed based on the decoupling technique. Moreover, a co-design scheme of controller gain and event-triggered matrix is obtained based on the linear matrix inequality technique. Finally, two examples are used to illustrate the validity and feasibility of the presented method.

Keywords: Dynamic event-triggered mechanism, exponential synchronization, neural networks, non-fragile controller.

IJCAS
July 2024

Vol. 22, No. 7, pp. 2055~2340

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