Input-output stability of linear consensus processes

In a network of n agents, consensus means that all n agents reach an agreement on a specific value of some quantity via local interactions. A linear consensus process can typically be modeled by a discrete-time linear recursion equation or a continuous-time linear differential equation, whose equilibria include nonzero states of the form a1 where a is a constant and 1 is a column vector in Rn whose entries all equal 1. Using a suitably defined semi-norm, this paper extends the standard notion of input-output stability from linear systems to linear recursions and differential equations of this type. Sufficient conditions for input-output consensus stability are provided. Connections between uniform bounded-input, bounded-output consensus stability and uniform exponential consensus stability are established. Certain types of additive perturbation to a linear consensus process are considered.

[1]  David Evans,et al.  Localization for mobile sensor networks , 2004, MobiCom '04.

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

[3]  Jie Lin,et al.  The multi-agent rendezvous problem , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[4]  Ming Cao,et al.  Interacting with Networks: How Does Structure Relate to Controllability in Single-Leader, Consensus Networks? , 2012, IEEE Control Systems.

[5]  Daniel A. Spielman,et al.  Accelerated Gossip Algorithms for Distributed Computation , 2006 .

[6]  Asuman E. Ozdaglar,et al.  Distributed Subgradient Methods for Multi-Agent Optimization , 2009, IEEE Transactions on Automatic Control.

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

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

[9]  Alexey S. Matveev,et al.  Stability of continuous-time consensus algorithms for switching networks with bidirectional interaction , 2013, 2013 European Control Conference (ECC).

[10]  Kenneth E. Barner,et al.  Convergence of Consensus Models With Stochastic Disturbances , 2010, IEEE Transactions on Information Theory.

[11]  Stephen P. Boyd,et al.  Distributed average consensus with least-mean-square deviation , 2007, J. Parallel Distributed Comput..

[12]  Asuman E. Ozdaglar,et al.  Constrained Consensus and Optimization in Multi-Agent Networks , 2008, IEEE Transactions on Automatic Control.

[13]  K. Johansson ROBUST CONSENSUS FOR CONTINUOUS-TIME , 2013 .

[14]  Javad Lavaei,et al.  Quantized Consensus by Means of Gossip Algorithm , 2012, IEEE Transactions on Automatic Control.

[15]  Sonia Martínez,et al.  Coverage control for mobile sensing networks , 2002, IEEE Transactions on Robotics and Automation.

[16]  Michael Chertkov,et al.  Synchronization in complex oscillator networks and smart grids , 2012, Proceedings of the National Academy of Sciences.

[17]  Luc Moreau,et al.  Stability of multiagent systems with time-dependent communication links , 2005, IEEE Transactions on Automatic Control.

[18]  Mathias Bürger,et al.  On the Robustness of Uncertain Consensus Networks , 2014, IEEE Transactions on Control of Network Systems.

[19]  Tamer Basar,et al.  Robust Distributed Averaging: When are Potential-Theoretic Strategies Optimal? , 2014, IEEE Transactions on Automatic Control.

[20]  João Pedro Hespanha,et al.  Linear Systems Theory , 2009 .

[22]  Brian D. O. Anderson,et al.  Reaching a Consensus in a Dynamically Changing Environment: Convergence Rates, Measurement Delays, and Asynchronous Events , 2008, SIAM J. Control. Optim..

[23]  Behrouz Touri,et al.  Product of Random Stochastic Matrices , 2011, IEEE Transactions on Automatic Control.

[24]  Shaoshuai Mou,et al.  Deterministic Gossiping , 2011, Proceedings of the IEEE.

[25]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[26]  B. Anderson,et al.  The Contraction Coefficient of a Complete Gossip Sequence , 2010 .

[27]  Angelia Nedic,et al.  On Convergence Rate of Weighted-Averaging Dynamics for Consensus Problems , 2017, IEEE Transactions on Automatic Control.

[28]  Brian D. O. Anderson,et al.  The Multi-Agent Rendezvous Problem. Part 1: The Synchronous Case , 2007, SIAM J. Control. Optim..

[29]  John N. Tsitsiklis,et al.  Convergence of Type-Symmetric and Cut-Balanced Consensus Seeking Systems , 2011, IEEE Transactions on Automatic Control.

[30]  A. Stephen Morse,et al.  Accelerated linear iterations for distributed averaging , 2011, Annu. Rev. Control..

[31]  L. Moreau,et al.  Stability of continuous-time distributed consensus algorithms , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[32]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[33]  Yongcan Cao,et al.  Distributed Coordinated Tracking With Reduced Interaction via a Variable Structure Approach , 2012, IEEE Transactions on Automatic Control.

[34]  Tamer Basar,et al.  Internal stability of linear consensus processes , 2014, 53rd IEEE Conference on Decision and Control.

[35]  Mireille E. Broucke,et al.  Stabilisation of infinitesimally rigid formations of multi-robot networks , 2009, Int. J. Control.

[36]  Ιωαννησ Τσιτσικλησ,et al.  PROBLEMS IN DECENTRALIZED DECISION MAKING AND COMPUTATION , 1984 .

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

[38]  Ji Liu,et al.  Design and analysis of distributed averaging with quantized communication , 2014, 53rd IEEE Conference on Decision and Control.

[39]  Randal W. Beard,et al.  Consensus seeking in multiagent systems under dynamically changing interaction topologies , 2005, IEEE Transactions on Automatic Control.

[40]  Brian D. O. Anderson,et al.  Agreeing Asynchronously , 2008, IEEE Transactions on Automatic Control.

[41]  Bo Liu,et al.  A new approach to the stability analysis of continuous-time distributed consensus algorithms , 2013, Neural Networks.

[42]  E. Seneta Non-negative Matrices and Markov Chains , 2008 .

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