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Robust consensus tracking of linear multiagent systems with input saturation and input‐additive uncertainties
Author(s) -
Wang Qingling,
Sun Changyin,
Xin Xin
Publication year - 2016
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.3690
Subject(s) - riccati equation , algebraic riccati equation , nonlinear system , multi agent system , control theory (sociology) , parameterized complexity , a priori and a posteriori , parametric statistics , consensus , bounded function , computer science , lyapunov function , algebraic graph theory , mathematics , algebraic connectivity , mathematical optimization , graph , algorithm , control (management) , differential equation , theoretical computer science , artificial intelligence , mathematical analysis , philosophy , statistics , physics , epistemology , quantum mechanics , laplacian matrix
Summary The problem of robust global consensus tracking of linear multiagent systems with input saturation and input‐additive uncertainties is investigated in this paper. By using the parametric Lyapunov equation approach and an existing dynamic gain scheduling technique, a new distributed nonlinear‐gain scheduling consensus‐trackining algorithm is developed to solve this problem. Under the assumption that each agent is asymptotically null controllable with bounded control, it is shown that the robust global consensus tracking can be achieved under the undirected graph provided that its generated graph contains a directed spanning tree. Compared with the existing algebraic Riccati equation approach, which requires the online solution of a parameterized algebraic Riccati equation, all the parameters in the proposed nonlinear algorithm are offline determined a priori . Finally, numerical examples are provided to validate the theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.