Sampled-data synchronization control for chaotic neural networks subject to actuator saturation

In this paper, the sampled-data control is applied to synchronize chaotic neural networks subject to actuator saturation. By employing a time-dependent Lyapunov functional that captures the characteristic information of actual sampling pattern, we derive a local stability condition for the synchroni...

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Bibliographic Details
Published inNeurocomputing (Amsterdam) Vol. 260; pp. 25 - 31
Main Authors Zeng, Hong-Bing, Teo, Kok Lay, He, Yong, Xu, Honglei, Wang, Wei
Format Journal Article
LanguageEnglish
Published Elsevier B.V 18.10.2017
Subjects
Actuator saturation
Neural networks
Regional synchronization
Sampled-data control
Sampled-data control
Regional synchronization
Neural networks
Actuator saturation
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Summary:In this paper, the sampled-data control is applied to synchronize chaotic neural networks subject to actuator saturation. By employing a time-dependent Lyapunov functional that captures the characteristic information of actual sampling pattern, we derive a local stability condition for the synchronization error systems. By this condition, we design a sampled-data controller to regionally synchronize the drive neural networks and response neural networks subject to actuator saturation. Moreover, an optimization method is given to design the desired sampled-data controller such that the set of admissible initial conditions is maximized. A numerical example is given to demonstrate the effectiveness and merits of the proposed design technique.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2017.02.063