Consensus of discrete-time multi-agent systems with nonlinear local rules and time-varying delays

In a multi-agent system (MAS), the agents are often considered to be autonomous entities, such as robots or software programs, each under the influence of a local rule, representing its interaction with other agents. Over the past few years, most research in the study of discrete-time MAS's concentrates on linear local rules. However, local interactions between agents are more likely to be governed by nonlinear rules with time-varying delays. This paper investigates the consensus of discrete-time MAS's with nonlinear local rules and time-varying delays. Based on a representative model, we obtain some basic criteria for the consensus of such MAS's. These results cover several existing results as special cases. Moreover, the above criteria are applied to the consensus of the classical Vicsek model with time-varying delays. Simulation results are presented to validate the obtained criteria.

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

[2]  J. Wolfowitz Products of indecomposable, aperiodic, stochastic matrices , 1963 .

[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]  Huaiqing Wang,et al.  Multi-agent coordination using nearest neighbor rules: revisiting the Vicsek model , 2004, ArXiv.

[6]  J.N. Tsitsiklis,et al.  Convergence in Multiagent Coordination, Consensus, and Flocking , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[7]  Zhixin Liu,et al.  Connectivity and synchronization of Vicsek model , 2008, Science in China Series F: Information Sciences.

[8]  Andrey V. Savkin,et al.  Coordinated collective motion of Groups of autonomous mobile robots: analysis of Vicsek's model , 2004, IEEE Transactions on Automatic Control.

[9]  Guanrong Chen,et al.  A time-varying complex dynamical network model and its controlled synchronization criteria , 2005, IEEE Transactions on Automatic Control.

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

[11]  I. Couzin,et al.  Emerging collective behaviors of animal groups , 2008, 2008 7th World Congress on Intelligent Control and Automation.

[12]  John N. Tsitsiklis,et al.  On the Nonexistence of Quadratic Lyapunov Functions for Consensus Algorithms , 2007, IEEE Transactions on Automatic Control.

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

[14]  Guanrong Chen,et al.  A time-varying complex dynamical network model and its controlled synchronization criteria , 2004, IEEE Trans. Autom. Control..

[15]  V. Blondel,et al.  Convergence of different linear and non-linear Vicsek models , 2006 .

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

[17]  Qin Li,et al.  RELAXED CONDITIONS FOR CONSENSUS IN MULTI-AGENT COORDINATION , 2008, J. Syst. Sci. Complex..