Resilient consensus of switched multi-agent systems

Abstract This letter considers the resilient consensus problem for switched multi-agent systems composed of continuous-time and discrete-time subsystems. We propose a switched filtering strategy for cooperative nodes based upon available local information, withstanding the threat of non-cooperative nodes. We provide conditions that guarantee resilient consensus in the presence of locally bounded Byzantine nodes in directed networks under arbitrary switching. Resilient scaled consensus and resilient scaled formation generation problems for switched multi-agent systems are solved as generalizations. Simulations are also provided to illustrate the effectiveness of the theoretical results.

[1]  Hideaki Ishii,et al.  Consensus of second-order multi-agent systems in the presence of locally bounded faults , 2015, Syst. Control. Lett..

[2]  Shreyas Sundaram,et al.  Resilient Asymptotic Consensus in Robust Networks , 2013, IEEE Journal on Selected Areas in Communications.

[3]  Yilun Shang,et al.  Hybrid consensus for averager-copier-voter networks with non-rational agents , 2018 .

[4]  Yungang Liu,et al.  Consensus via time-varying feedback for uncertain nonlinear multi-agent systems with rather coarse input disturbances , 2017, Syst. Control. Lett..

[5]  Wenwu Yu,et al.  An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination , 2012, IEEE Transactions on Industrial Informatics.

[6]  J. Danskin.  The Theory of Max-Min, with Applications , 1966 .

[7]  S. Shankar Sastry,et al.  Research Challenges for the Security of Control Systems , 2008, HotSec.

[8]  Long Wang,et al.  Finite-time formation control for multi-agent systems , 2009, Autom..

[9]  Long Wang,et al.  Containment control of switched multi-agent systems , 2015, Int. J. Control.

[10]  Long Wang,et al.  Recent Advances in Consensus of Multi-Agent Systems: A Brief Survey , 2017, IEEE Transactions on Industrial Electronics.

[11]  Yilun Shang,et al.  Scaled consensus of switched multi-agent systems , 2019, IMA J. Math. Control. Inf..

[12]  Derong Liu,et al.  Lie algebraic stability analysis for switched systems with continuous-time and discrete-time subsystems , 2006, IEEE Trans. Circuits Syst. II Express Briefs.

[13]  Yilun Shang,et al.  On the Delayed Scaled Consensus Problems , 2017 .

[14]  Vijay Kumar,et al.  Resilient Flocking for Mobile Robot Teams , 2017, IEEE Robotics and Automation Letters.

[15]  Yilun Shang,et al.  Deffuant model of opinion formation in one-dimensional multiplex networks , 2015 .

[16]  Lei Zou,et al.  Output-feedback H2 / H∞ consensus control for stochastic time-varying multi-agent systems with (x, u, v)-dependent noises , 2017, Syst. Control. Lett..

[17]  Shreyas Sundaram,et al.  Robustness of information diffusion algorithms to locally bounded adversaries , 2011, 2012 American Control Conference (ACC).

[18]  Shreyas Sundaram,et al.  A Notion of Robustness in Complex Networks , 2015, IEEE Transactions on Control of Network Systems.

[19]  Magnus Egerstedt,et al.  Graph Theoretic Methods in Multiagent Networks , 2010, Princeton Series in Applied Mathematics.

[20]  Long Wang,et al.  Consensus of Switched Multiagent Systems , 2016, IEEE Transactions on Circuits and Systems II: Express Briefs.

[21]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[22]  Sandip Roy,et al.  Scaled consensus , 2015, Autom..

[23]  Xue Lin,et al.  Finite-Time Consensus of Switched Multiagent Systems , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[24]  Xiongxiong He,et al.  Secure consensus control for multiagent systems with attacks and communication delays , 2016, IEEE/CAA Journal of Automatica Sinica.

[25]  Seif Haridi,et al.  Distributed Algorithms , 1992, Lecture Notes in Computer Science.

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

[27]  G. Deffuant,et al.  An energy-like indicator to assess opinion resilience , 2017 .