A novel analysis on the efficiency of hierarchy among leader-following systems

In a recent NATURE paper, Nagy et al. find a well-defined hierarchy among the individuals of the pigeon flock, which may lead to a rapid decision making in the directional choice dynamics of the flock. Motivated by this interesting discovery, we present a novel analysis on the efficiency of the hierarchical topology among the leader-following systems in this paper. To this end, we first propose a measurement of the convergence rate of leader-following consensus, and then connect the convergence rates with the communication topologies of leader-following systems. It is proved that the hierarchical network organization can achieve the best performance in terms of convergence rates. It is also established that the connections between the leader and the followers have effective impacts on increasing the convergence rates. Extensive numerical results are provided to show the effectiveness of our conclusions.

[1]  Jinde Cao,et al.  Consensus of a leader-following multi-agent system with negative weights and noises , 2014 .

[2]  Wei Xing Zheng,et al.  Consensus of multiple second-order vehicles with a time-varying reference signal under directed topology , 2011, Autom..

[3]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[4]  Long Wang,et al.  Asynchronous Consensus in Continuous-Time Multi-Agent Systems With Switching Topology and Time-Varying Delays , 2006, IEEE Transactions on Automatic Control.

[5]  Karl Henrik Johansson,et al.  A graph-theoretic approach on optimizing informed-node selection in multi-agent tracking control , 2014 .

[6]  I. Couzin,et al.  Effective leadership and decision-making in animal groups on the move , 2005, Nature.

[7]  Vicsek,et al.  Novel type of phase transition in a system of self-driven particles. , 1995, Physical review letters.

[8]  Jianbin Qiu,et al.  A novel approach to coordination of multiple robots with communication failures via proximity graph , 2011, Autom..

[9]  Maurizio Porfiri,et al.  Leader-follower consensus over numerosity-constrained random networks , 2012, Autom..

[10]  Jinde Cao,et al.  Interval stability of time-varying two-dimensional hierarchical discrete-time multi-agent systems , 2015 .

[11]  Karl Henrik Johansson,et al.  Using Hierarchical Decomposition to Speed Up Average Consensus , 2008 .

[12]  D. Helbing,et al.  Leadership, consensus decision making and collective behaviour in humans , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.

[13]  Jiangping Hu,et al.  Brief paper: Leader-following consensus for multi-agent systems via sampled-data control , 2011 .

[14]  T. Vicsek,et al.  Hierarchical group dynamics in pigeon flocks , 2010, Nature.

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

[16]  Yeung Sam Hung,et al.  Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case , 2010, Autom..

[17]  Magnus Egerstedt,et al.  Distributed containment control with multiple stationary or dynamic leaders in fixed and switching directed networks , 2012, Autom..

[18]  G. Parisi,et al.  Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a field study , 2007, Proceedings of the National Academy of Sciences.

[19]  R. Olfati-Saber Ultrafast consensus in small-world networks , 2005, Proceedings of the 2005, American Control Conference, 2005..

[20]  Jinde Cao,et al.  Consensus of nonlinear multi-agent systems with observer-based protocols , 2014, Syst. Control. Lett..

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

[22]  Manfredi Maggiore,et al.  State Agreement for Continuous-Time Coupled Nonlinear Systems , 2007, SIAM J. Control. Optim..

[23]  L. Y. Kolotilina Bounds and Inequalities for the Perron Root of a Nonnegative Matrix , 2004 .

[24]  Wei Xing Zheng,et al.  Distributed control gains design for consensus in multi-agent systems with second-order nonlinear dynamics , 2013, Autom..

[25]  Manfredi Maggiore,et al.  Necessary and sufficient graphical conditions for formation control of unicycles , 2005, IEEE Transactions on Automatic Control.

[26]  Changbin Yu,et al.  Cluster consensus control of generic linear multi-agent systems under directed topology with acyclic partition , 2013, Autom..

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

[28]  Mehran Mesbahi,et al.  On maximizing the second smallest eigenvalue of a state-dependent graph Laplacian , 2006, IEEE Transactions on Automatic Control.

[29]  A. Czirók,et al.  Collective Motion , 1999, physics/9902023.

[30]  Jinde Cao,et al.  Hierarchical Cooperative Control for Multiagent Systems With Switching Directed Topologies , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[31]  Charles R. Johnson,et al.  Topics in Matrix Analysis , 1991 .

[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]  Huijun Gao,et al.  A Sufficient Condition for Convergence of Sampled-Data Consensus for Double-Integrator Dynamics With Nonuniform and Time-Varying Communication Delays , 2012, IEEE Transactions on Automatic Control.

[34]  Stephen P. Boyd,et al.  Fast linear iterations for distributed averaging , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[35]  Long Wang,et al.  Group consensus in multi-agent systems with switching topologies and communication delays , 2010, Syst. Control. Lett..

[36]  Jianhong Shen,et al.  Cucker–Smale Flocking under Hierarchical Leadership , 2006, q-bio/0610048.