Pinning Synchronization of Complex Switching Networks With a Leader of Nonzero Control Inputs

The evolution of the target system (leader) in pinning-controlled complex networks may need to be regulated by some control inputs for performing various practical tasks, e.g., obstacle avoidance, tracking highly maneuverable target, and so on. Motivated by this observation, we shall investigate the global pinning synchronization problems for complex switching networks for which the target system is subject to nonzero control inputs. First, using the idea of unit vector function method, a discontinuous coupling law is designed. With the aid of stability theory for switched systems, it is theoretically shown that synchronization in the network under this discontinuous coupling law can be achieved by choosing sufficiently large coupling strengths if the average dwell time (ADT) is bounded below by a positive constant. Second, we use the boundary layer method to design a continuous-coupling law. It has been theoretically shown that the synchronization error is ultimately uniformly bounded (UUB) under this continuous-coupling law. The chattering effect is also avoided in real implementation by using this continuous-coupling law. Furthermore, for networks with unknown external disturbances and unmodeled dynamics, neuro-adaptive-based coupling laws are designed to ensure that the synchronization error of the networks with undirected switching communication topologies under these laws is UUB. The obtained theoretical results are finally validated by performing numerical simulation on coupling Chua’s circuit systems.

[1]  Tianping Chen,et al.  Synchronization in Networks of Linearly Coupled Dynamical Systems via Event-Triggered Diffusions , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[2]  Xiang Li,et al.  Global stabilization of complex networks with digraph topologies via a local pinning algorithm , 2010, Autom..

[3]  Junan Lu,et al.  Adaptive synchronization of an uncertain complex dynamical network , 2006, IEEE Transactions on Automatic Control.

[4]  Guo-Xing Wen,et al.  Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[5]  Long Cheng,et al.  Neural-Network-Based Adaptive Leader-Following Control for Multiagent Systems With Uncertainties , 2010, IEEE Transactions on Neural Networks.

[6]  Xiang Li,et al.  Control and Flocking of Networked Systems via Pinning , 2010, IEEE Circuits and Systems Magazine.

[7]  Tianping Chen,et al.  New approach to synchronization analysis of linearly coupled ordinary differential systems , 2006 .

[8]  Daniel W. C. Ho,et al.  Clustered Event-Triggered Consensus Analysis: An Impulsive Framework , 2016, IEEE Transactions on Industrial Electronics.

[9]  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.

[10]  Yuezu Lv,et al.  Distributed adaptive output feedback consensus protocols for linear systems on directed graphs with a leader of bounded input , 2016, Autom..

[11]  P DeLellis,et al.  Synchronization and control of complex networks via contraction, adaptation and evolution , 2010, IEEE Circuits and Systems Magazine.

[12]  Hong Chen,et al.  Approximation capability in C(R¯n) by multilayer feedforward networks and related problems , 1995, IEEE Trans. Neural Networks.

[13]  Mario di Bernardo,et al.  On QUAD, Lipschitz, and Contracting Vector Fields for Consensus and Synchronization of Networks , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[14]  Ziyang Meng,et al.  Synchronization of Coupled Nonlinear Dynamical Systems: Interplay Between Times of Connectivity and Integral of Lipschitz Gain , 2016, IEEE Transactions on Circuits and Systems II: Express Briefs.

[15]  Xinghuo Yu,et al.  Sliding Mode Control Made Smarter: A Computational Intelligence Perspective , 2017, IEEE Systems, Man, and Cybernetics Magazine.

[16]  Tianping Chen,et al.  Consensus problem in directed networks of multi-agents via nonlinear protocols☆ , 2009 .

[17]  Hong Chen,et al.  Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems , 1995, IEEE Trans. Neural Networks.

[18]  T. Carroll,et al.  MASTER STABILITY FUNCTIONS FOR SYNCHRONIZED COUPLED SYSTEMS , 1999 .

[19]  Wei Xing Zheng,et al.  Robust $H_{\infty }$ Group Consensus for Interacting Clusters of Integrator Agents , 2017, IEEE Transactions on Automatic Control.

[20]  Tianping Chen,et al.  Pinning Complex Networks by a Single Controller , 2007, IEEE Transactions on Circuits and Systems I: Regular Papers.

[21]  Lihua Xie,et al.  Distributed Tracking Control for Linear Multiagent Systems With a Leader of Bounded Unknown Input , 2013, IEEE Transactions on Automatic Control.

[22]  Wenwu Yu,et al.  Distributed Adaptive Control of Synchronization in Complex Networks , 2012, IEEE Transactions on Automatic Control.

[23]  Gang Feng,et al.  Containment control of linear multi‐agent systems with multiple leaders of bounded inputs using distributed continuous controllers , 2013, ArXiv.

[24]  Jinde Cao,et al.  Multiagent Systems on Multilayer Networks: Synchronization Analysis and Network Design , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[25]  Mario di Bernardo,et al.  Contraction Theory and Master Stability Function: Linking Two Approaches to Study Synchronization of Complex Networks , 2009, IEEE Transactions on Circuits and Systems II: Express Briefs.

[26]  Robert Shorten,et al.  On common noise-induced synchronization in complex networks with state-dependent noise diffusion processes , 2018 .

[27]  Guanghui Wen,et al.  Neuro-Adaptive Consensus Tracking of Multiagent Systems With a High-Dimensional Leader , 2017, IEEE Transactions on Cybernetics.

[28]  C. K. Michael Tse,et al.  An Encryption Scheme Based on Synchronization of Two-Layered Complex Dynamical Networks , 2016, IEEE Transactions on Circuits and Systems I: Regular Papers.

[29]  C. Wu Synchronization in networks of nonlinear dynamical systems coupled via a directed graph , 2005 .

[30]  Giovanni Russo,et al.  On Synchronization in Continuous-Time Networks of Nonlinear Nodes With State-Dependent and Degenerate Noise Diffusion , 2019, IEEE Transactions on Automatic Control.

[31]  Gang Feng,et al.  Synchronization of Complex Dynamical Networks With Time-Varying Delays Via Impulsive Distributed Control , 2010, IEEE Transactions on Circuits and Systems I: Regular Papers.

[32]  Wenwu Yu,et al.  Synchronizing nonlinear complex networks via switching disconnected topology , 2016, Autom..

[33]  Xiang Li,et al.  Towards a temporal network analysis of interactive WiFi users , 2012, ArXiv.

[34]  Guanghui Wen,et al.  Pinning a Complex Network to Follow a Target System With Predesigned Control Inputs , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[35]  M. Stone The Generalized Weierstrass Approximation Theorem , 1948 .

[36]  Hong Chen,et al.  Approximations of continuous functionals by neural networks with application to dynamic systems , 1993, IEEE Trans. Neural Networks.

[37]  R. Plemmons M-matrix characterizations.I—nonsingular M-matrices , 1977 .

[38]  Vadim I. Utkin,et al.  A control engineer's guide to sliding mode control , 1999, IEEE Trans. Control. Syst. Technol..

[39]  Guanghui Wen,et al.  On Constructing Multiple Lyapunov Functions for Tracking Control of Multiple Agents With Switching Topologies , 2019, IEEE Transactions on Automatic Control.

[40]  Mario di Bernardo,et al.  Novel decentralized adaptive strategies for the synchronization of complex networks , 2009, Autom..

[41]  Xiang Li,et al.  Pinning a complex dynamical network to its equilibrium , 2004, IEEE Trans. Circuits Syst. I Regul. Pap..

[42]  Zhiyong Geng,et al.  Adaptive consensus tracking for linear multi‐agent systems with heterogeneous unknown nonlinear dynamics , 2016 .