Regular Paper

International Journal of Control, Automation and Systems 2019; 17(9): 2430-2440

Published online May 27, 2019

https://doi.org/10.1007/s12555-018-0678-5

© The International Journal of Control, Automation, and Systems

Improved Synchronization Criteria for Chaotic Neural Networks with Sampled-data Control Subject to Actuator Saturation

Seung Hoon Lee, Myeong Jin Park, Oh Min Kwon*, and Palanisamy Selvaraj

Chungbuk National University

Abstract

In this paper, the synchronization problem for chaotic neural networks with sampled-data control and actuator saturation is investigated. By constructing a suitable time-dependent function and utilizing a modified free-matrix-based integral inequality, a sampled-data synchronization criterion for chaotic neural networks is derived as the framework of linear matrix inequalities. Based on the first result, a design method of sampled-data controller subject to actuator saturation for chaotic neural networks is introduced through an optimization method which enlarges the set of admissible initial conditions. The superiority and validity of the proposed results will be verified through comparing with the existing results in a numerical example.

Keywords Actuator saturation, chaotic neural networks, Lyapunov method, sampled-data control.

Article

Regular Paper

International Journal of Control, Automation and Systems 2019; 17(9): 2430-2440

Published online September 1, 2019 https://doi.org/10.1007/s12555-018-0678-5

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

Improved Synchronization Criteria for Chaotic Neural Networks with Sampled-data Control Subject to Actuator Saturation

Seung Hoon Lee, Myeong Jin Park, Oh Min Kwon*, and Palanisamy Selvaraj

Chungbuk National University

Abstract

In this paper, the synchronization problem for chaotic neural networks with sampled-data control and actuator saturation is investigated. By constructing a suitable time-dependent function and utilizing a modified free-matrix-based integral inequality, a sampled-data synchronization criterion for chaotic neural networks is derived as the framework of linear matrix inequalities. Based on the first result, a design method of sampled-data controller subject to actuator saturation for chaotic neural networks is introduced through an optimization method which enlarges the set of admissible initial conditions. The superiority and validity of the proposed results will be verified through comparing with the existing results in a numerical example.

Keywords: Actuator saturation, chaotic neural networks, Lyapunov method, sampled-data control.

IJCAS
March 2025

Vol. 23, No. 3, pp. 683~972

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