Neural-networks-based distributed output regulation of multi-agent systems with nonlinear dynamics

This paper deals with the output regulation problem of the nonlinear multi-agent systems based on dynamic neural networks. Assume that the models of following agents in the considered systems are unknown, and the state of the leader agent is not completely measurable for each follower. By employing Lyapunov approach, a dynamic neural network is established to approximate the systems of the following agents. Based on the dynamic neural network, a state feedback control law is designed guaranteeing the following agents can asymptotically track the reference generated by an exosystem. The exosystem is regarded as the active leaders in the multi-agent systems. A numerical simulation example is provided to demonstrate the effectiveness of the obtained results.

[1]  Zhong-Ping Jiang,et al.  Multi-agent coordination with general linear models: A distributed output regulation approach , 2010, IEEE ICCA 2010.

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

[3]  Jie Huang,et al.  Approximate output regulation of spherical inverted pendulum by neural network control , 2012, Neurocomputing.

[4]  Chee Peng Lim,et al.  A neural network-based multi-agent classifier system , 2009, Neurocomputing.

[5]  N. Rouche,et al.  Stability Theory by Liapunov's Direct Method , 1977 .

[6]  Manolis A. Christodoulou,et al.  Adaptive control of unknown plants using dynamical neural networks , 1994, IEEE Trans. Syst. Man Cybern..

[7]  Richard M. Murray,et al.  Information flow and cooperative control of vehicle formations , 2004, IEEE Transactions on Automatic Control.

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

[9]  Bruno Sinopoli,et al.  Kalman filtering with intermittent observations , 2004, IEEE Transactions on Automatic Control.

[10]  Timothy W. McLain,et al.  Coordination Variables and Consensus Building in Multiple Vehicle Systems , 2004 .

[11]  Yiguang Hong,et al.  Coordination for a Group of Autonomous Mobile Agents with Multiple Leaders , 2006, 2006 Chinese Control Conference.

[12]  Yiguang Hong,et al.  Distributed Observers Design for Leader-Following Control of Multi-Agent Networks (Extended Version) , 2017, 1801.00258.

[13]  V. Gazi.  Formation control of a multi-agent system using non-linear servomechanism , 2005 .

[14]  Randal W. Beard,et al.  Distributed Consensus in Multi-vehicle Cooperative Control - Theory and Applications , 2007, Communications and Control Engineering.

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

[16]  Pierre-Alexandre Bliman,et al.  Average consensus problems in networks of agents with delayed communications , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[17]  Luc Moreau,et al.  Stability of multiagent systems with time-dependent communication links , 2005, IEEE Transactions on Automatic Control.

[18]  Jia Liu,et al.  Coordinative control of multi-agent systems using distributed nonlinear output regulation , 2012 .

[19]  Jia Yingmin.  Aggregation of Multi-Agent systems with group leaders , 2006 .

[20]  Zhong-Ping Jiang,et al.  A distributed control approach to robust output regulation of networked linear systems , 2010, IEEE ICCA 2010.

[21]  Stephen P. Boyd,et al.  Linear Matrix Inequalities in Systems and Control Theory , 1994 .

[22]  Guy-Bart Stan,et al.  Fast Consensus Via Predictive Pinning Control , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

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

[24]  A. Isidori,et al.  Output regulation of nonlinear systems , 1990 .

[25]  Jie Huang,et al.  A general framework for tackling the output regulation problem , 2004, IEEE Transactions on Automatic Control.