Title :
Model reference adaptive consensus control
Author :
Miyasato, Yoshihiko
Author_Institution :
Dept. of Math. Anal. & Stat. Inference, Inst. of Stat. Math., Tokyo, Japan
Abstract :
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.
Keywords :
control nonlinearities; control system synthesis; model reference adaptive control systems; multivariable systems; robust control; uncertain systems; adaptation mechanism; backstepping procedure; consensus tracking; model reference adaptive consensus control design method; multiagent systems; restricted information network structure; state variable filters; uncertain system parameters; unknown linear processes; Adaptation models; Multi-agent systems; Robustness; Symmetric matrices; Trajectory;
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
Print_ISBN :
978-1-4673-5714-2
DOI :
10.1109/CDC.2013.6760874
