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Sampled‐data output feedback leader‐following consensus for a class of nonlinear multi‐agent systems with input unmodeled dynamics
Author(s) -
Mao Jun,
Yan Tianhong,
Huang Shipei,
Li Shuo,
Jiao Jiange
Publication year - 2021
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5467
Subject(s) - backstepping , control theory (sociology) , lipschitz continuity , nonlinear system , observer (physics) , computer science , lyapunov function , multi agent system , class (philosophy) , consensus , function (biology) , control (management) , mathematics , adaptive control , artificial intelligence , mathematical analysis , physics , quantum mechanics , evolutionary biology , biology
This investigation focuses on the sampled‐data output feedback consensus problem for a class of second‐order nonlinear multi‐agent systems with uncertain time‐varying control coefficient and input unmodeled dynamics. In the considered multi‐agent system, the nonlinearities are more stronger than those under the Lipschitz condition, and the existence of the uncertain time‐varying control coefficient causes the invalidation of the full‐order observer. Under such situation, the reduced‐order observers are designed, and the filters are introduced to handle the uncertainties of the input unmodeled dynamics. By adopting the backstepping method, the sampled‐data consensus protocols are developed, and by selecting an appropriate Lyapunov function candidate, we can demonstrate that the practical leader‐following consensus can be achieved for the considered multi‐agent system by the developed protocols with the suitable design constants and an allowable sampling period. Finally, the effectiveness of the proposed consensus method is illustrated by two simulation examples.