Robust consensus tracking for heterogeneous linear multi-agent systems with disturbances

The robust consensus tracking problem is studied in this paper for a class of heterogeneous linear multi-agent systems with disturbances and directed communication topology graphs. A new kind of consensus protocol based on cooperative observers and relative states among neighbouring agents is first proposed. With the help of the designed cooperative observers, the agents in the group could reject the disturbances efficiently if at least one agent can measure the disturbances directly in a strongly connected graph. Furthermore, when the relative states between neighboring agents are unavailable, a distributed observer-type consensus tracking protocol based on relative output measurements is proposed. By using tools from Lyapunov stability theory, some sufficient criteria for achieving consensus tracking are obtained. Simulations are finally provided to illustrate the performance and effectiveness of the theoretical results.

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

[2]  Wenwu Yu,et al.  Robust adaptive flocking control of nonlinear multi-agent systems , 2010, 2010 IEEE International Symposium on Computer-Aided Control System Design.

[3]  Fernando Paganini,et al.  Scalable laws for stable network congestion control , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[4]  Xianping Liu,et al.  Further Results on Consensus of Second-Order Multi-Agent Systems With Exogenous Disturbance , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[5]  Guangming Xie,et al.  Consensus control for a class of networks of dynamic agents , 2007 .

[6]  Lin Huang,et al.  Consensus of Multiagent Systems and Synchronization of Complex Networks: A Unified Viewpoint , 2016, IEEE Transactions on Circuits and Systems I: Regular Papers.

[7]  Okyay Kaynak,et al.  Robust and adaptive backstepping control for nonlinear systems using RBF neural networks , 2004, IEEE Transactions on Neural Networks.

[8]  Guoguang Wen,et al.  Distributed cooperative control for multi-agent systems , 2012 .

[9]  Jiangping Hu,et al.  Leader-following coordination of multi-agent systems with coupling time delays , 2007, 0705.0401.

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

[11]  Jie Huang,et al.  Cooperative global output regulation of heterogeneous second-order nonlinear uncertain multi-agent systems , 2013, Autom..

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

[13]  Jie Huang,et al.  Cooperative Output Regulation of Linear Multi-Agent Systems , 2012, IEEE Transactions on Automatic Control.

[14]  Wenwu Yu,et al.  Some necessary and sufficient conditions for second-order consensus in multi-agent dynamical systems , 2010, Autom..

[15]  Guanghui Wen,et al.  Distributed H ∞ consensus of multi-agent systems: a performance region-based approach , 2012, Int. J. Control.

[16]  Richard M. Murray,et al.  DISTRIBUTED COOPERATIVE CONTROL OF MULTIPLE VEHICLE FORMATIONS USING STRUCTURAL POTENTIAL FUNCTIONS , 2002 .

[17]  Francesco Bullo,et al.  Coordination and Geometric Optimization via Distributed Dynamical Systems , 2003, SIAM J. Control. Optim..

[18]  Guanghui Wen,et al.  Distributed cooperative anti-disturbance control of multi-agent systems: an overview , 2017, Science China Information Sciences.

[19]  Richard M. Murray,et al.  INFORMATION FLOW AND COOPERATIVE CONTROL OF VEHICLE FORMATIONS , 2002 .

[20]  Zhengtao Ding,et al.  Consensus Disturbance Rejection With Disturbance Observers , 2015, IEEE Transactions on Industrial Electronics.

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

[22]  Zhenxing Zhang,et al.  Consensus of second‐order multi‐agent systems with exogenous disturbances , 2011 .

[23]  Daizhan Cheng,et al.  Lyapunov-Based Approach to Multiagent Systems With Switching Jointly Connected Interconnection , 2007, IEEE Transactions on Automatic Control.

[24]  Wei Ren,et al.  Distributed consensus of linear multi-agent systems with adaptive dynamic protocols , 2011, Autom..