New Decentralised Event-Triggered Consensus Strategy for Single and Double Integrator Multi-Agent Systems

This paper proposes new decentralised event-triggering conditions for single- and double integrator multi-agent systems. The developed conditions are based on the relative ratio of the state measurement error and norm of a state function for actuating the controller updates. With higher limits on the maximum tolerable state measurement error, the controller is shown to reduce the actuation updates and hence, the use of available resources. The network topology is assumed to be undirected and connected. The inter-event intervals are shown to be strictly positive for all agents to eliminate the zeno phenomenon. The theoretical concepts are further demonstrated through numerical comparisons and illustrative simulations.

[1]  Ella M. Atkins,et al.  Distributed multi‐vehicle coordinated control via local information exchange , 2007 .

[2]  Mohammed Essaaidi,et al.  Applications of Multi-Agent Systems in Smart Grids: A survey , 2014, 2014 International Conference on Multimedia Computing and Systems (ICMCS).

[3]  Xiaoyuan Luo,et al.  Event-Triggered Consensus Control for Second-Order Multi-Agent Systems With/Without Input Time Delay , 2019, IEEE Access.

[4]  Dapeng Yang,et al.  Decentralized event-triggered consensus for linear multi-agent systems under general directed graphs , 2016, Autom..

[5]  Karl Henrik Johansson,et al.  Event-triggered control for multi-agent systems , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[6]  Zhiping Shi,et al.  Distributed Observer-Based Leader-Following Consensus Control for Second-Order Stochastic Multi-Agent Systems , 2018, IEEE Access.

[7]  R. Jackson.  Inequalities , 2007, Algebra for Parents.

[8]  Paulo Tabuada,et al.  Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks , 2007, IEEE Transactions on Automatic Control.

[9]  Ming Liu,et al.  Event-triggered fault tolerant control for spacecraft formation attitude synchronization with limited data communication , 2019, Eur. J. Control.

[10]  Jinhu Lü,et al.  Adaptive Diffusion Processes of Time-Varying Local Information on Networks , 2018, IEEE Transactions on Circuits and Systems II: Express Briefs.

[11]  Wei Ren,et al.  Information consensus in multivehicle cooperative control , 2007, IEEE Control Systems.

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

[13]  Jan Lunze,et al.  Event-based control: A state-feedback approach , 2009, 2009 European Control Conference (ECC).

[14]  W. P. M. H. Heemels,et al.  Analysis of event-driven controllers for linear systems , 2008, Int. J. Control.

[15]  Paulo Tabuada,et al.  To Sample or not to Sample: Self-Triggered Control for Nonlinear Systems , 2008, IEEE Transactions on Automatic Control.

[16]  Pu Zhang,et al.  Multi-Agent Fault-Tolerant Control Based on Distributed Adaptive Consensus , 2019, IEEE Access.

[17]  E. Yaz.  Linear Matrix Inequalities In System And Control Theory , 1998, Proceedings of the IEEE.

[18]  Shengyuan Xu,et al.  Event-triggered consensus control for second-order multi-agent systems , 2015 .

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

[20]  Vahid Rezaei,et al.  Event-triggered robust cooperative stabilization in nonlinearly interconnected multiagent systems , 2019, Eur. J. Control.

[21]  S.D.J. McArthur,et al.  Multi-Agent Systems for Power Engineering Applications—Part II: Technologies, Standards, and Tools for Building Multi-agent Systems , 2007, IEEE Transactions on Power Systems.