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Distributed Observer‐based Stabilization of Nonlinear Multi‐agent Systems with Sampled‐data Control
Author(s) -
Wan Ying,
Cao Jinde,
Alsaedi Ahmed,
Hayat Tasawar
Publication year - 2017
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1415
Subject(s) - control theory (sociology) , lipschitz continuity , observer (physics) , nonlinear system , multi agent system , algebraic graph theory , lyapunov stability , mathematics , matrix (chemical analysis) , stability (learning theory) , linear matrix inequality , computer science , mathematical optimization , control (management) , physics , quantum mechanics , artificial intelligence , mathematical analysis , materials science , machine learning , composite material
In this paper, the distributed observer‐based stabilization problem of multi‐agent systems under a directed graph is investigated. Distributed observer‐based control protocol with sampled‐data information is proposed. The dynamics of each agent contain a nonlinear part, which is supposed to be general Lipschitz. In order to stabilize the states of the whole network, all the nodes utilize the relative output estimation error at sampling instants and only a small fraction of nodes use the absolute output estimation error additionally. By virtue of the input‐to‐state stability (ISS) property and the Lyapunov stability theory, an algorithm to design the control gain matrix, observer gain matrix, coupling strength as well as the allowable sampling period are derived. The conditions are in the form of LMIs and algebraic inequality, which are simple in form and easy to verify. Some further discussions about the solvability of obtained linear matrix inequalities (LMIs) are also given. Lastly, an example is simulated to further validate the obtained results.