Finite-Time Stabilization for Stochastic Inertial Neural Networks with Time-Delay via Nonlinear Delay Controller

This paper pays close attention to the problem of finite-time stabilization related to stochastic inertial neural networks with or without time-delay. By establishing proper Lyapunov-Krasovskii functional and making use of matrix inequalities, some sufficient conditions on finite-time stabilization...

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Published inMathematical problems in engineering Vol. 2018; no. 2018; pp. 1 - 11
Main Authors Zhu, Shasha, Chen, Guici, Wang, Yuanyuan, Li, Deyi
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 01.01.2018
Hindawi
John Wiley & Sons, Inc
Subjects
Automation
Control theory
Controllers
Delay
Engineering
Feedback control
Investigations
Linear matrix inequalities
Matrix methods
Neural networks
Noise
Nonlinear control
Nonlinear feedback
Physics
Researchers
Signal processing
Stabilization
Time functions
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ISSN1024-123X
1563-5147
DOI10.1155/2018/2939425

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Summary:This paper pays close attention to the problem of finite-time stabilization related to stochastic inertial neural networks with or without time-delay. By establishing proper Lyapunov-Krasovskii functional and making use of matrix inequalities, some sufficient conditions on finite-time stabilization are obtained and the stochastic settling-time function is also estimated. Furthermore, in order to achieve the finite-time stabilization, both delayed and nondelayed nonlinear feedback controllers are designed, respectively, in terms of solutions to a set of linear matrix inequalities (LMIs). Finally, a numerical example is provided to demonstrate the correction of the theoretical results and the effectiveness of the proposed control design method.
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ISSN:1024-123X
1563-5147
DOI:10.1155/2018/2939425