Finite-time boundedness, -gain analysis and control of Markovian jump switched neural networks with additive time-varying delays

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• 作者：M. Syed Ali^a ; ^{syedgru@gmail.com} ; S. Saravanan^a ; ^{saravanantvu@gmail.com} ; Jinde Cao^b ; ^{jdcao@seu.edu.cn}
• 关键词：Average dwell time approach ; Finite-time boundedness ; Finite-time control design ; L2L2-gain analysis ; Lyapunov&ndash ; Krasovskii functional ; Switched neural networks
• 刊名：Nonlinear Analysis: Hybrid Systems
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：23
• 期：Complete
• 页码：27-43
• 全文大小：472 K
• 卷排序：23

文摘

This paper is concerned with the problem of finite-time boundedness, L2L2 gain analysis and control of Markovian jump switched neural networks (MJSNNs) with additive time-varying delays. Sufficient conditions to guarantee finite-time bounded of MJSNNs with additive time-varying delays are presented. These conditions are delay-dependent and are given in terms of linear matrix inequalities (LMIs). Moreover, finite-time L2L2-gain analysis of switched neural networks with additive time-varying delays are given to measure its disturbance tolerance capability in the fixed time interval. In addition finite-time control of MJSNNs is studied. Detailed proofs are accomplished by using Lyapunov-functionals and average dwell time approach (ADT). Finally, numerical example is given to demonstrate the effectiveness of the proposed approach.