Synchronization of General Chaotic Neural Networks With Nonuniform Sampling and Packet Missing: A Switched System Approach

This paper is concerned with the exponential synchronization issue of general chaotic neural networks subject to nonuniform sampling and control packet missing in the frame of the zero-input strategy. Based on this strategy, we make use of the switched system model to describe the synchronization error system. First, when the missing of control packet does not occur, an exponential stability criterion with less conservatism is established for the resultant synchronization error systems via a superior time-dependent Lyapunov functional and the convex optimization approach. The characteristics induced by nonuniform sampling can be used to the full because of the structure and property of the constructed Lyapunov functional, that is not necessary to be positive definite except sampling times. Then, a criterion is obtained to guarantee that the general chaotic neural networks are synchronous exponentially when the missing of control packet occurs by means of the average dwell-time technique. An explicit expression of the sampled-data static output feedback controller is also gained. Finally, the effectiveness of the proposed new design methods is shown via two examples.

[1]  Diana Baader,et al.  Stability Analysis And Robust Control Of Time Delay Systems , 2016 .

[2]  Huaguang Zhang,et al.  Robust Global Exponential Synchronization of Uncertain Chaotic Delayed Neural Networks via Dual-Stage Impulsive Control , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[3]  P. Shi Filtering on sampled-data systems with parametric uncertainty , 1998, IEEE Trans. Autom. Control..

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

[5]  Peng Shi,et al.  Exponential Synchronization of Neural Networks With Discrete and Distributed Delays Under Time-Varying Sampling , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[6]  Carroll,et al.  Synchronization in chaotic systems. , 1990, Physical review letters.

[7]  Ju H. Park,et al.  Non-fragile synchronization of neural networks with time-varying delay and randomly occurring controller gain fluctuation , 2013, Appl. Math. Comput..

[8]  Zidong Wang,et al.  Global exponential stability of generalized recurrent neural networks with discrete and distributed delays , 2006, Neural Networks.

[9]  Tingwen Huang,et al.  Passivity and Synchronization of Linearly Coupled Reaction-Diffusion Neural Networks With Adaptive Coupling , 2015, IEEE Transactions on Cybernetics.

[10]  Meiqin Liu,et al.  Optimal exponential synchronization of general chaotic delayed neural networks: An LMI approach , 2009, Neural Networks.

[11]  Kun Liu,et al.  Wirtinger's inequality and Lyapunov-based sampled-data stabilization , 2012, Autom..

[12]  Wei Xing Zheng,et al.  An Improved Stabilization Method for Sampled-Data Control Systems With Control Packet Loss , 2012, IEEE Transactions on Automatic Control.

[13]  Yong He,et al.  Stability Analysis and Robust Control of Time-Delay Systems , 2010 .

[14]  Luca Schenato,et al.  To Zero or to Hold Control Inputs With Lossy Links? , 2009, IEEE Transactions on Automatic Control.

[15]  Emilia Fridman,et al.  Robust sampled-data stabilization of linear systems: an input delay approach , 2004, Autom..

[16]  Zhigang Zeng,et al.  Design and Analysis of High-Capacity Associative Memories Based on a Class of Discrete-Time Recurrent Neural Networks , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[17]  Zidong Wang,et al.  Synchronization of Coupled Neutral-Type Neural Networks With Jumping-Mode-Dependent Discrete and Unbounded Distributed Delays , 2013, IEEE Transactions on Cybernetics.

[18]  Jun Wang,et al.  Attractivity Analysis of Memristor-Based Cellular Neural Networks With Time-Varying Delays , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[19]  Wen-an Zhang,et al.  Modelling and control of networked control systems with both network-induced delay and packet-dropout , 2008, Autom..

[20]  Tingwen Huang,et al.  Stabilization for sampled-data systems under noisy sampling interval , 2016, Autom..

[21]  Yang Cao,et al.  Observer-Based Consensus Tracking of Nonlinear Agents in Hybrid Varying Directed Topology , 2017, IEEE Transactions on Cybernetics.

[22]  Choon Ki Ahn,et al.  New sets of criteria for exponential L2-L∞ stability of Takagi-Sugeno fuzzy systems combined with hopfield neural networks , 2013 .

[23]  Chenguang Yang,et al.  Global Neural Dynamic Surface Tracking Control of Strict-Feedback Systems With Application to Hypersonic Flight Vehicle , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[24]  Zidong Wang,et al.  A Stochastic Sampled-Data Approach to Distributed $H_{\infty }$ Filtering in Sensor Networks , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[25]  Peng Shi,et al.  Sampled-Data Synchronization of Chaotic Lur'e Systems With Time Delays , 2013, IEEE Transactions on Neural Networks and Learning Systems.

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

[27]  Zidong Wang,et al.  Stability and Synchronization of Discrete-Time Markovian Jumping Neural Networks With Mixed Mode-Dependent Time Delays , 2009, IEEE Transactions on Neural Networks.

[28]  Renquan Lu,et al.  Passivity-based non-fragile control for Markovian jump systems with aperiodic sampling , 2015, Syst. Control. Lett..

[29]  Pin-Lin Liu,et al.  DELAY-DEPENDENT ROBUST STABILITY ANALYSIS FOR RECURRENT NEURAL NETWORKS WITH TIME-VARYING DELAY , 2013 .

[30]  Tingwen Huang,et al.  Passivity-based synchronization of a class of complex dynamical networks with time-varying delay , 2015, Autom..

[31]  Chen Yul Network-Based H_∞ Output Tracking Control for a Type of Discrete Time Systems , 2014 .

[32]  Yan Huang,et al.  A New Class of Chaotic Simple Three-Neuron Cellular Neural Networks , 2006, Int. J. Bifurc. Chaos.

[33]  Peng Shi,et al.  Local Synchronization of Chaotic Neural Networks With Sampled-Data and Saturating Actuators , 2014, IEEE Transactions on Cybernetics.

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

[35]  T. Su,et al.  Delay-dependent stability analysis for recurrent neural networks with time-varying delay , 2008 .

[36]  Huijun Gao,et al.  Network-Based ${{\cal H}}_{\!\!\!\infty }$ Output Tracking Control , 2008, IEEE Transactions on Automatic Control.

[37]  Peng Shi,et al.  Sampled-Data Fuzzy Control of Chaotic Systems Based on a T–S Fuzzy Model , 2014, IEEE Transactions on Fuzzy Systems.

[38]  Zidong Wang,et al.  Sampled-Data Synchronization Control of Dynamical Networks With Stochastic Sampling , 2012, IEEE Transactions on Automatic Control.

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

[40]  Emilia Fridman,et al.  A refined input delay approach to sampled-data control , 2010, Autom..

[41]  Huai-Ning Wu,et al.  Pinning Control Strategies for Synchronization of Linearly Coupled Neural Networks With Reaction–Diffusion Terms , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[42]  Wen-an Zhang,et al.  Stabilization of Sampled-Data Control Systems With Control Inputs Missing , 2010, IEEE Transactions on Automatic Control.