Impulsive Consensus of Multiagent Systems With Limited Bandwidth Based on Encoding–Decoding

Energy constrains are always significant to be considered in control of multiagent systems. Besides, nonlinear phenomena are often involved into such systems. In this paper, we discuss the impulsive consensus problem of nonlinear multiagent systems via impulsive protocol with limited bandwidth communication based on encoding–decoding. The scheme based on encoding–decoding with impulsive protocol is introduced to multiagent systems in general directed networks topology of which the graph is strongly connected. The impulsive protocols and limited bandwidth communication enhance the performance on energy saving and the involvement of nonlinear dynamics could suit more real-world cases. The design of encoders and decoders is presented, which is the key to achieve the goal that the information exchanged is subject to limited bandwidth communication. The conditions to guarantee the impulsive consensus and the conditions to avoid quantizer saturation are obtained. Moreover, the convergence rate of such multiagent systems are also characterized by the analysis of the exponential consensus. The numerical simulations are presented to support the theoretical results.

[1]  Yongqiang Guan,et al.  Quantized consensus of second-order multi-agent systems via impulsive control , 2017, Neurocomputing.

[2]  George J. Pappas,et al.  Flocking in Fixed and Switching Networks , 2007, IEEE Transactions on Automatic Control.

[3]  Haibo Jiang,et al.  Impulsive synchronization of networked nonlinear dynamical systems , 2010 .

[4]  Yu Lin,et al.  Synchronization of stochastic impulsive discrete-time delayed networks via pinning control , 2018, Neurocomputing.

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

[6]  Ruggero Carli,et al.  Average consensus on networks with quantized communication , 2009 .

[7]  Daniel W. C. Ho,et al.  Fault-Tolerant Consensus of Multi-Agent System With Distributed Adaptive Protocol , 2015, IEEE Transactions on Cybernetics.

[8]  Hongjie Li,et al.  Leader-following consensus of nonlinear multi-agent systems with mixed delays and uncertain parameters via adaptive pinning intermittent control , 2016 .

[9]  Bo Liu,et al.  Pinning Consensus in Networks of Multiagents via a Single Impulsive Controller , 2013, IEEE Transactions on Neural Networks and Learning Systems.

[10]  Guanrong Chen,et al.  A time-varying complex dynamical network model and its controlled synchronization criteria , 2005, IEEE Transactions on Automatic Control.

[11]  Lihua Xie,et al.  Distributed Coordination of Multi-Agent Systems With Quantized-Observer Based Encoding-Decoding , 2012, IEEE Transactions on Automatic Control.

[12]  Chuandong Li,et al.  Second-order consensus of discrete-time multi-agent systems in directed networks with nonlinear dynamics via impulsive protocols , 2018, Neurocomputing.

[13]  Yu Zhang,et al.  Impulsive Control of Discrete Systems With Time Delay , 2009, IEEE Transactions on Automatic Control.

[14]  Antoine Girard,et al.  Coordination in networks of linear impulsive agents , 2014, 53rd IEEE Conference on Decision and Control.

[15]  Lihua Xie,et al.  Quantized Leaderless and Leader-Following Consensus of High-Order Multi-Agent Systems With Limited Data Rate , 2016, IEEE Transactions on Automatic Control.

[16]  Guangming Xie,et al.  Second-order consensus of multi-agent systems in the cooperation-competition network with switching topologies: A time-delayed impulsive control approach , 2013, Syst. Control. Lett..

[17]  Jinde Cao,et al.  $M$-Matrix Strategies for Pinning-Controlled Leader-Following Consensus in Multiagent Systems With Nonlinear Dynamics , 2013, IEEE Transactions on Cybernetics.

[18]  Jie Chen,et al.  Distributed Consensus of Second-Order Multi-Agent Systems With Heterogeneous Unknown Inertias and Control Gains Under a Directed Graph , 2016, IEEE Transactions on Automatic Control.

[19]  Long Wang,et al.  Leader-Following Consensus for Linear and Lipschitz Nonlinear Multiagent Systems With Quantized Communication , 2017, IEEE Transactions on Cybernetics.

[20]  Xinghuo Yu,et al.  Pulse-Modulated Intermittent Control in Consensus of Multiagent Systems , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[21]  Peng Shi,et al.  Control of Nonlinear Networked Systems With Packet Dropouts: Interval Type-2 Fuzzy Model-Based Approach , 2015, IEEE Transactions on Cybernetics.

[22]  W. Ren Consensus strategies for cooperative control of vehicle formations , 2007 .

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

[24]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

[25]  Shihua Chen,et al.  Synchronization of impulsively coupled complex systems with delay. , 2011, Chaos.

[26]  Jinhu Lü,et al.  Robust consensus of multi-agent systems with time-varying delays in noisy environment , 2011 .

[27]  Farzaneh Abdollahi,et al.  Consensus Problem in High-Order Multiagent Systems With Lipschitz Nonlinearities and Jointly Connected Topologies , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[28]  Zhiyong Chen,et al.  Semi-Global Consensus of Nonlinear Second-Order Multi-Agent Systems With Measurement Output Feedback , 2014, IEEE Transactions on Automatic Control.

[29]  Zhao Yang Dong,et al.  Consensus analysis of multiagent systems with second-order nonlinear dynamics and general directed topology: An event-triggered scheme , 2016, Inf. Sci..

[30]  Xiaoqing Lu,et al.  Finite-Time Distributed Tracking Control for Multi-Agent Systems With a Virtual Leader , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[31]  Fuad E. Alsaadi,et al.  An Integrated Approach to Global Synchronization and State Estimation for Nonlinear Singularly Perturbed Complex Networks , 2015, IEEE Transactions on Cybernetics.

[32]  R. Srikant,et al.  Quantized Consensus , 2006, 2006 IEEE International Symposium on Information Theory.

[33]  Lihua Xie,et al.  Quantized leaderless and leader-following consensus of high-order multi-agent systems with limited data rate , 2013, 52nd IEEE Conference on Decision and Control.

[34]  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.