Adaptive architectures for resilient control of networked multiagent systems in the presence of misbehaving agents

ABSTRACT Control algorithms of networked multiagent systems are generally computed distributively without having a centralised entity monitoring the activity of agents; and therefore, unforeseen adverse conditions such as uncertainties or attacks to the communication network and/or failure of agent-wise components can easily result in system instability and prohibit the accomplishment of system-level objectives. In this paper, we study resilient coordination of networked multiagent systems in the presence of misbehaving agents, i.e. agents that are subject to exogenous disturbances that represent a class of adverse conditions. In particular, a distributed adaptive control architecture is presented for directed and time-varying graph topologies to retrieve a desired networked multiagent system behaviour. Apart from the existing relevant literature that make specific assumptions on the graph topology and/or the fraction of misbehaving agents, we show that the considered class of adverse conditions can be mitigated by the proposed adaptive control approach that utilises a local state emulator – even if all agents are misbehaving. Illustrative numerical examples are provided to demonstrate the theoretical findings.

[1]  C.N. Hadjicostis,et al.  Distributed function calculation via linear iterations in the presence of malicious agents — Part II: Overcoming malicious behavior , 2008, 2008 American Control Conference.

[2]  Jeff S. Shamma,et al.  Cooperative Control of Distributed Multi-Agent Systems: Shamma/Cooperative Control of Distributed Multi-Agent Systems , 2007 .

[3]  E. Lavretsky,et al.  Adaptive Compensation of Control Dependent Modeling Uncertainties using Time-Scale Separation , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[4]  P. Parks A new proof of the Routh-Hurwitz stability criterion using the second method of Liapunov , 1962, Mathematical Proceedings of the Cambridge Philosophical Society.

[5]  Randal W. Beard,et al.  Distributed Consensus in Multi-vehicle Cooperative Control - Theory and Applications , 2007, Communications and Control Engineering.

[6]  C.N. Hadjicostis,et al.  Distributed function calculation via linear iterations in the presence of malicious agents — Part I: Attacking the network , 2008, 2008 American Control Conference.

[7]  Jeff S. Shamma,et al.  Cooperative Control of Distributed Multi-Agent Systems , 2008 .

[8]  Magnus Egerstedt,et al.  Control of multiagent systems under persistent disturbances , 2012, 2012 American Control Conference (ACC).

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

[10]  Torsten Jeinsch,et al.  A characterization of parity space and its application to robust fault detection , 1999, IEEE Trans. Autom. Control..

[11]  Andrea Bacciotti,et al.  An invariance principle for nonlinear switched systems , 2005, Syst. Control. Lett..

[12]  Mi-Ching Tsai,et al.  Robust and Optimal Control , 2014 .

[13]  Wassim M. Haddad,et al.  Stability and Control of Large-Scale Dynamical Systems: A Vector Dissipative Systems Approach , 2011 .

[14]  Karl Henrik Johansson,et al.  Distributed fault detection for interconnected second-order systems , 2011, Autom..

[15]  Tansel Yucelen,et al.  Resilient networked multiagent systems: A distributed adaptive control approachy , 2014, 53rd IEEE Conference on Decision and Control.

[16]  Tansel Yucelen,et al.  Consensus protocols for networked multiagent systems with a uniformly continuous quasi-resetting architecture , 2013, 2013 American Control Conference.

[17]  Antonio Bicchi,et al.  Consensus Computation in Unreliable Networks: A System Theoretic Approach , 2010, IEEE Transactions on Automatic Control.

[18]  M. Egerstedt,et al.  Motion probes for fault detection and recovery in networked control systems , 2008, 2008 American Control Conference.

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

[20]  E. Panteley,et al.  On global uniform asymptotic stability of nonlinear time-varying systems in cascade , 1998 .

[21]  Shreyas Sundaram,et al.  Resilient continuous-time consensus in fractional robust networks , 2013, 2013 American Control Conference.

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

[23]  Roy M. Howard,et al.  Linear System Theory , 1992 .

[24]  Antonio Bicchi,et al.  Distributed intrusion detection for secure consensus computations , 2007, 2007 46th IEEE Conference on Decision and Control.

[25]  Paul M. Frank,et al.  Fault diagnosis in dynamic systems: theory and application , 1989 .

[26]  Jorge Cortes,et al.  Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms , 2009 .

[27]  D. Bernstein Matrix Mathematics: Theory, Facts, and Formulas , 2009 .