Open AccessOutput consensus of high‐order linear multi‐agent systems with time‐varying delays
Author(s) -
Jiang Xiangli,
Xia Guihua,
Feng Zhiguang
Publication year - 2019
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2018.5945
Subject(s) - control theory (sociology) , observability , mathematics , invertible matrix , consensus , multi agent system , convergence (economics) , scalar (mathematics) , lyapunov function , interval (graph theory) , linear matrix inequality , computer science , mathematical optimization , control (management) , nonlinear system , artificial intelligence , economics , physics , geometry , quantum mechanics , combinatorics , pure mathematics , economic growth
In this study, the problem of output consensus control for high‐order continuous‐time linear multi‐agent systems with interval time‐varying delays is investigated. The observability decomposition technique is employed to design the output consensus protocols which are the collections of delayed output information from neighbouring agents. On the basis of invertible transformations, output consensus for the concerned dynamical agents is transformed into the problem of asymptotical stability analysis for some lower dimensional subsystems. By introducing the prescribed convergence rate scalar into the constructed delay‐dependent Lyapunov functionals, the framework for output consensus analysis is theoretically derived. Benefitting from the method of slack matrix variables, sufficient conditions are obtained in terms of linear matrix inequalities to design the protocol gain matrices which can guarantee the property of output consensus. Moreover, the output consensus function determined merely by the initial states of dynamic agents and consensus protocol is presented without the influences of time‐varying delays. Numerical examples are exploited to illustrate the effectiveness of the derived results.