Model reference adaptive consensus control

A design method of model reference adaptive consensus control of multi-agent systems composed of unknown linear processes is presented in this paper. The proposed control scheme is constructed via a backstepping procedure and state variable filters together with a restricted information network structure among agents. It is shown that the resulting control system is robust to uncertain system parameters and that the desirable consensus tracking is achieved asymptotically or approximately via the adaptation mechanism.

[1]  Miroslav Krstic,et al.  Stabilization of Nonlinear Uncertain Systems , 1998 .

[2]  Yoshihiko Miyasato.  Stable adaptive controller design for uncertain phase shift , 2005, Annu. Rev. Control..

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

[4]  Wei Ren,et al.  Consensus algorithms are input-to-state stable , 2005, Proceedings of the 2005, American Control Conference, 2005..

[5]  Kar-Han Tan,et al.  Virtual structures for high-precision cooperative mobile robotic control , 1996, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96.

[6]  Yongcan Cao,et al.  Distributed coordinated tracking via a variable structure approach - part II: Swarm tracking , 2010, Proceedings of the 2010 American Control Conference.

[7]  R. Ordonez,et al.  Swarm Tracking Using Artificial Potentials and Sliding Mode Control , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[8]  Chien Chern Cheah,et al.  Region-based shape control for a swarm of robots , 2009, Autom..

[9]  C. Tomlin,et al.  Decentralized optimization, with application to multiple aircraft coordination , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[10]  Koji Tsumura,et al.  Consensus via Distributed Adaptive Control , 2011 .

[11]  Liu Hsu,et al.  Adaptive Formation Control Using Artificial Potentials for Euler-Lagrange Agents , 2008 .

[12]  Kevin L. Moore,et al.  Decentralized adaptive scheduling using consensus variables , 2007 .

[13]  Tucker R. Balch,et al.  Behavior-based formation control for multirobot teams , 1998, IEEE Trans. Robotics Autom..

[14]  Yoshihiko Miyasato.  Adaptive H∞ formation control for Euler-Lagrange systems , 2010, 49th IEEE Conference on Decision and Control (CDC).

[15]  Guangming Xie,et al.  Leader-following formation control of multiple mobile vehicles , 2007 .

[16]  Yoshihiko Miyasato.  Adaptive Nonlinear H∞ Control for Processes with Bounded Variations of Parameters- General Forms and General Relative Degree Case , 2001 .

[17]  Richard M. Murray,et al.  Recent Research in Cooperative Control of Multivehicle Systems , 2007 .

[18]  Y. Miyasato.  Adaptive nonlinear H/sub /spl infin// control for processes with bounded variations of parameters-general relative degree case , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[19]  Kevin L. Moore,et al.  High-Order and Model Reference Consensus Algorithms in Cooperative Control of MultiVehicle Systems , 2007 .

[20]  Shuzhi Sam Ge,et al.  Decentralized cooperative control for swarm agents with high-order dynamics , 2009, 2009 IEEE International Conference on Automation and Logistics.