Partial-Nodes-Based State Estimation for Complex Networks With Unbounded Distributed Delays

In this brief, the new problem of partial-nodes-based (PNB) state estimation problem is investigated for a class of complex network with unbounded distributed delays and energy-bounded measurement noises. The main novelty lies in that the states of the complex network are estimated through measurement outputs of a fraction of the network nodes. Such fraction of the nodes is determined by either the practical availability or the computational necessity. The PNB state estimator is designed such that the error dynamics of the network state estimation is exponentially ultimately bounded in the presence of measurement errors. Sufficient conditions are established to ensure the existence of the PNB state estimators and then the explicit expression of the gain matrices of such estimators is characterized. When the network measurements are free of noises, the main results specialize to the case of exponential stability for error dynamics. Numerical examples are presented to verify the theoretical results.

[1]  Xian-Wu Zou,et al.  Dynamic fluctuation model of complex networks with weight scaling behavior and its application to airport networks , 2014 .

[2]  Zidong Wang,et al.  Synchronization and State Estimation for Discrete-Time Complex Networks With Distributed Delays , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[3]  R. Solé,et al.  Evolving protein interaction networks through gene duplication. , 2003, Journal of theoretical biology.

[4]  Seiichi Nakamori,et al.  Signal estimation with multiple delayed sensors using covariance information , 2010, Digit. Signal Process..

[5]  Ioannis G Kevrekidis,et al.  Gene regulatory networks: a coarse-grained, equation-free approach to multiscale computation. , 2005, The Journal of chemical physics.

[6]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[7]  Daniel W. C. Ho,et al.  Finite-Time Cluster Synchronization of T–S Fuzzy Complex Networks With Discontinuous Subsystems and Random Coupling Delays , 2015, IEEE Transactions on Fuzzy Systems.

[8]  Xiao Fan Wang,et al.  Pinning control of complex networked systems: A decade after and beyond , 2014, Annu. Rev. Control..

[9]  V. Latora,et al.  Complex networks: Structure and dynamics , 2006 .

[10]  Albert-László Barabási,et al.  Observability of complex systems , 2013, Proceedings of the National Academy of Sciences.

[11]  Peng Shi,et al.  Joint state filtering and parameter estimation for linear stochastic time-delay systems , 2011, Signal Process..

[12]  Pagavathigounder Balasubramaniam,et al.  Delay-dependent H∞ filtering for complex dynamical networks with time-varying delays in nonlinear function and network couplings , 2016, Signal Process..

[13]  Xiao Fan Wang,et al.  Decentralized Adaptive Pinning Control for Cluster Synchronization of Complex Dynamical Networks , 2013, IEEE Transactions on Cybernetics.

[14]  Jinde Cao,et al.  Synchronization of Randomly Coupled Neural Networks With Markovian Jumping and Time-Delay , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[15]  Frank L. Lewis,et al.  Off-Policy Integral Reinforcement Learning Method to Solve Nonlinear Continuous-Time Multiplayer Nonzero-Sum Games , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[16]  Daniel W. C. Ho,et al.  Pinning Synchronization in T–S Fuzzy Complex Networks With Partial and Discrete-Time Couplings , 2015, IEEE Transactions on Fuzzy Systems.

[17]  Zidong Wang,et al.  $H_{\infty}$ State Estimation for Complex Networks With Uncertain Inner Coupling and Incomplete Measurements , 2013, IEEE Transactions on Neural Networks and Learning Systems.

[18]  Frank L. Lewis,et al.  Multiple Actor-Critic Structures for Continuous-Time Optimal Control Using Input-Output Data , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[19]  Panos J. Antsaklis,et al.  Control and Communication Challenges in Networked Real-Time Systems , 2007, Proceedings of the IEEE.

[20]  Huijun Gao,et al.  Event-Triggered State Estimation for Complex Networks With Mixed Time Delays via Sampled Data Information: The Continuous-Time Case , 2015, IEEE Transactions on Cybernetics.

[21]  Zidong Wang,et al.  On synchronization of coupled neural networks with discrete and unbounded distributed delays , 2008, Int. J. Comput. Math..

[22]  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.

[23]  Zidong Wang,et al.  Global Synchronization for Discrete-Time Stochastic Complex Networks With Randomly Occurred Nonlinearities and Mixed Time Delays , 2010, IEEE Transactions on Neural Networks.

[24]  Jun Hu,et al.  A variance-constrained approach to recursive state estimation for time-varying complex networks with missing measurements , 2016, Autom..

[25]  G. T. Heydt,et al.  A Linear State Estimation Formulation for Smart Distribution Systems , 2013, IEEE Transactions on Power Systems.

[26]  M. Aldana Boolean dynamics of networks with scale-free topology , 2003 .

[27]  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.

[28]  Albert-László Barabási,et al.  Internet: Diameter of the World-Wide Web , 1999, Nature.

[29]  Chavdar Dangalchev,et al.  Generation models for scale-free networks , 2004 .

[30]  Guoqiang Hu,et al.  Pinning Synchronization of Directed Networks With Switching Topologies: A Multiple Lyapunov Functions Approach , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[31]  Yan-Wu Wang,et al.  Global Synchronization of Complex Dynamical Networks Through Digital Communication With Limited Data Rate , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[32]  Tianping Chen,et al.  Synchronization of Complex Networks via Aperiodically Intermittent Pinning Control , 2015, IEEE Transactions on Automatic Control.

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

[34]  Eckehard Schöll,et al.  Synchronization-desynchronization transitions in complex networks: an interplay of distributed time delay and inhibitory nodes. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[35]  S. Strogatz Exploring complex networks , 2001, Nature.