Synchronized Control of Chaotic Neural Networks With Actuator Saturation

This paper investigates the chaotic synchronization of neural networks via sampled-data control with actuator saturation. First, a new generalized looped-functional is constructed by considering valid information from <inline-formula> <tex-math notation="LaTeX">t_{k} </tex-m...

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Bibliographic Details
Published inIEEE access Vol. 12; pp. 73599 - 73607
Main Authors Liao, Wen-Qi, Zeng, Hong-Bing, Xiao, Hui-Qin, Liang, Jin-Ming
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
actuator saturation
Actuators
Chaotic neural networks
Convexity
Linear matrix inequalities
Lyapunov methods
Neural networks
sampled-data control
Stability
Symmetric matrices
Synchronism
Synchronization
Vectors
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Summary:This paper investigates the chaotic synchronization of neural networks via sampled-data control with actuator saturation. First, a new generalized looped-functional is constructed by considering valid information from <inline-formula> <tex-math notation="LaTeX">t_{k} </tex-math></inline-formula> to t and from t to <inline-formula> <tex-math notation="LaTeX">t_{k+1} </tex-math></inline-formula>. Then, local stability conditions for the synchronization error system are given based on the Lyapunov stability theory. A sampled-data controller is designed to achieve the synchronization of the driving neural network and the response neural network by solving the convex optimization problem with given conditions. The proposed method's effectiveness and practicality are numerically verified.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3402815