Exponential H∞ synchronization of switching fuzzy systems with time-varying delay and impulses

Abstract This paper studies the problem of exponential H ∞ synchronization of switching fuzzy systems with time-varying delay and impulses via maximum, minimum dwell time. The switching fuzzy model has locally Takagi and Sugeno (T–S) fuzzy models and switches them according to states, external variables and/or time. By introducing the concept of maximum, minimum dwell time and a modified two-side direction relation between the number of switchings and the maximum, minimum dwell time, a normal L 2 norm bound constraint is derived. By using the matrix decomposition method and reciprocal convex combination, and combining with the Wirtinger-based inequality, which gives a sharper upper bound than the Jensen's inequality, some new sufficient criteria are obtained to guarantee that the error system without impulses and with impulses is globally exponentially stable with an H ∞ performance index γ, respectively. Three illustrative examples are provided to show the effectiveness of the results.

[1]  Jinde Cao,et al.  Sampled-Data $$H_{\infty }$$H∞ Synchronization of Chaotic Lur’e Systems with Time Delay , 2015, Circuits Syst. Signal Process..

[2]  Xiaodi Li,et al.  Stability of nonlinear differential systems with state-dependent delayed impulses , 2016, Autom..

[3]  Guoliang Chen,et al.  Improved passivity analysis for neural networks with Markovian jumping parameters and interval time-varying delays , 2015, Neurocomputing.

[4]  Xiaodi Li,et al.  LMI-based stability for singularly perturbed nonlinear impulsive differential systems with delays of small parameter , 2015, Appl. Math. Comput..

[5]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[6]  Jinde Cao,et al.  A unified synchronization criterion for impulsive dynamical networks , 2010, Autom..

[7]  Qinghua Zhou Global exponential stability of BAM neural networks with distributed delays and impulses , 2009 .

[8]  Jian-an Fang,et al.  Synchronization of hybrid impulsive and switching dynamical networks with delayed impulses , 2016 .

[9]  E. Vaadia,et al.  Synchronization in neuronal transmission and its importance for information processing. , 1994 .

[10]  Wei Xing Zheng,et al.  Exponential Stability Analysis for Delayed Neural Networks With Switching Parameters: Average Dwell Time Approach , 2010, IEEE Transactions on Neural Networks.

[11]  Quan Yin,et al.  H∞ Synchronization of Directed Complex Dynamical Networks with Mixed Time-Delays and Switching Structures , 2013, Circuits Syst. Signal Process..

[12]  A. Teel,et al.  Stability of delay impulsive systems with application to networked control systems , 2007, 2007 American Control Conference.

[13]  Yongming Li,et al.  Adaptive fuzzy output feedback control for MIMO switched nonlinear systems with prescribed performances , 2017, Fuzzy Sets Syst..

[14]  Daniel W. C. Ho,et al.  Pinning Stabilization of Linearly Coupled Stochastic Neural Networks via Minimum Number of Controllers , 2009, IEEE Transactions on Neural Networks.

[15]  Vladimir L. Kharitonov,et al.  Stability of Time-Delay Systems , 2003, Control Engineering.

[16]  Jinde Cao,et al.  Outer synchronization of partially coupled dynamical networks via pinning impulsive controllers , 2015, J. Frankl. Inst..

[17]  Min Wu,et al.  New Delay-dependent Stability Criteria for T-S Fuzzy Systems with a Time-varying Delay , 2008 .

[18]  Xinzhi Liu,et al.  Fault-tolerant synchronization for nonlinear switching systems with time-varying delay , 2017 .

[19]  Olga I. Moskalenko,et al.  On the use of chaotic synchronization for secure communication , 2009 .

[20]  Yingmin Jia,et al.  New approaches on stability criteria for neural networks with two additive time-varying delay components , 2013, Neurocomputing.

[21]  A. Arunkumar,et al.  Robust stochastic stability of discrete-time fuzzy Markovian jump neural networks. , 2014, ISA transactions.

[22]  Bo Hu,et al.  Disturbance attenuation properties of time-controlled switched systems , 2001, J. Frankl. Inst..

[23]  Jinde Cao,et al.  Synchronization in an Array of Output-Coupled Boolean Networks With Time Delay , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[24]  C. Ahn Delay-dependent state estimation for T-S fuzzy delayed Hopfield neural networks , 2010 .

[25]  Jun Zhao,et al.  Stability and L2-gain analysis for switched delay systems: A delay-dependent method , 2006, Autom..

[26]  Yong Wang,et al.  Improved exponential stability criteria for neural networks with time-varying delays , 2012, Neurocomputing.

[27]  S. Ge,et al.  Switched Linear Systems: Control and Design , 2005 .

[28]  Xinzhi Liu,et al.  Reduced-order fault detection filter design for switched nonlinear systems with time delay , 2012 .

[29]  R. Rakkiyappan,et al.  Impulsive controller design for exponential synchronization of delayed stochastic memristor-based recurrent neural networks , 2016, Neurocomputing.

[30]  Daniel Liberzon,et al.  Switching in Systems and Control , 2003, Systems & Control: Foundations & Applications.

[31]  João Pedro Hespanha,et al.  Exponential stability of impulsive systems with application to uncertain sampled-data systems , 2008, Syst. Control. Lett..

[32]  Qing-Long Han,et al.  Fault-Tolerant Master–Slave Synchronization for Lur'e Systems Using Time-Delay Feedback Control , 2009, IEEE Transactions on Circuits and Systems I: Regular Papers.

[33]  Wuneng Zhou,et al.  Robust synchronization for stochastic delayed complex networks with switching topology and unmodeled dynamics via adaptive control approach , 2013, Commun. Nonlinear Sci. Numer. Simul..

[34]  Xiaojie Su,et al.  Dissipativity-Based Filtering for Fuzzy Switched Systems With Stochastic Perturbation , 2016, IEEE Transactions on Automatic Control.

[35]  Zhi-Hong Guan,et al.  Passive stability and synchronization of complex spatio-temporal switching networks with time delays , 2009, Autom..

[36]  Wei Xing Zheng,et al.  Weighted H∞ model reduction for linear switched systems with time-varying delay , 2009, Autom..

[37]  Hongbin Zhang,et al.  Robust exponential H∞ filtering for discrete-time switched fuzzy systems , 2013, 2013 International Conference on Communications, Circuits and Systems (ICCCAS).

[38]  Zheng-Guang Wu,et al.  Robust $\mathcal{H}_{\infty}$ decentralized dynamic control for synchronization of a complex dynamical network with randomly occurring uncertainties , 2012 .

[39]  Carlos Silvestre,et al.  Stability of networked control systems with asynchronous renewal links: An impulsive systems approach , 2013, Autom..

[40]  Robin J. Evans,et al.  Hybrid Dynamical Systems: Controller and Sensor Switching Problems , 2012 .

[41]  T. Liao,et al.  H∞ synchronization of chaotic systems using output feedback control design , 2007 .

[42]  Jinde Cao,et al.  Finite-time boundedness, L2-gain analysis and control of Markovian jump switched neural networks with additive time-varying delays , 2017 .

[43]  Shouming Zhong,et al.  New passivity criteria for uncertain neural networks with time-varying delay , 2016, Neurocomputing.

[44]  Peng Shi,et al.  Stochastic Synchronization of Markovian Jump Neural Networks With Time-Varying Delay Using Sampled Data , 2013, IEEE Transactions on Cybernetics.

[45]  Lin Shi,et al.  Globally exponential stability for neural networks with time-varying delays , 2013, Appl. Math. Comput..

[46]  Zidong Wang,et al.  State estimation for discrete-time Markovian jumping neural networks with mixed mode-dependent delays ☆ , 2008 .