Flocking of Multi‐Agents Following a Leader with Adaptive Protocol in a Noisy Environment

This paper investigates the flocking problem of multi-agents following a leader with communication delays in a noisy environment. Based on potential fields and the LaSalle-type theorem for stochastic differential delay equations, by introducing the adaptive protocol compensating for the desired velocity, a new neighbor-based flocking protocol is proposed such that all the agents move with a virtual leader's velocity almost surely, and avoidance of collision between the agents is ensured. A numerical example is given to illustrate the effectiveness of the proposed methods.

[1]  X. Mao,et al.  A note on the LaSalle-type theorems for stochastic differential delay equations , 2002 .

[2]  Zengqiang Chen,et al.  Flocking of multi-agents with nonlinear inner-coupling functions , 2010 .

[3]  Wen Yang,et al.  Flocking in multi‐agent systems with multiple virtual leaders , 2008 .

[4]  Chunguang Li,et al.  Synchronization in general complex dynamical networks with coupling delays , 2004 .

[5]  Junan Lu,et al.  Pinning adaptive synchronization of a general complex dynamical network , 2008, Autom..

[6]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[7]  Tao Li,et al.  Consensus Conditions of Multi-Agent Systems With Time-Varying Topologies and Stochastic Communication Noises , 2010, IEEE Transactions on Automatic Control.

[8]  J. Toner,et al.  Hydrodynamics and phases of flocks , 2005 .

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

[10]  Hayakawa,et al.  Collective motion in a system of motile elements. , 1996, Physical review letters.

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

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

[13]  J. Toner,et al.  Flocks, herds, and schools: A quantitative theory of flocking , 1998, cond-mat/9804180.

[14]  Xiaofan Wang,et al.  Connectivity Preserving Flocking without Velocity Measurement , 2013 .

[15]  Xinzhi Liu,et al.  Stochastic consensus seeking with communication delays , 2011, Autom..

[16]  Xuerong Mao,et al.  Stochastic differential equations and their applications , 1997 .

[17]  A. Mogilner,et al.  A non-local model for a swarm , 1999 .

[18]  A. Ōkubo Dynamical aspects of animal grouping: swarms, schools, flocks, and herds. , 1986, Advances in biophysics.

[19]  Long Wang,et al.  Virtual leader approach to coordinated control of multiple mobile agents with asymmetric interactions , 2006 .

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

[21]  Zhiyong Chen,et al.  No-beacon collective circular motion of jointly connected multi-agents , 2011, Autom..

[22]  Xiao Fan Wang,et al.  Flocking of Multi-Agents With a Virtual Leader , 2009, IEEE Trans. Autom. Control..

[23]  B. Crowther,et al.  Flocking of autonomous unmanned air vehicles , 2003, The Aeronautical Journal (1968).

[24]  Zhong-Ping Jiang,et al.  Asynchronous Distributed Algorithms for Heading Consensus of Multi‐Agent Systems with Communication Delay , 2013 .

[25]  Chao Zhai,et al.  A General Alignment Repulsion Algorithm for Flocking of Multi-Agent Systems , 2011, IEEE Transactions on Automatic Control.

[26]  A. Friedman 17 – Stochastic Differential Games , 1976 .

[27]  Khac Duc Do,et al.  Formation control of multiple elliptic agents with limited sensing ranges , 2012 .

[28]  J. Ruan,et al.  Consensus in noisy environments with switching topology and time-varying delays , 2010 .

[29]  George J. Pappas,et al.  Flocking while preserving network connectivity , 2007, 2007 46th IEEE Conference on Decision and Control.