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Distributed adaptive output consensus control of a class of uncertain nonlinear multiagents systems
Author(s) -
Yang Yang,
Tan Jie
Publication year - 2018
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2894
Subject(s) - backstepping , nonlinear system , bounded function , control theory (sociology) , a priori and a posteriori , computer science , multi agent system , consensus , graph , directed graph , adaptive control , class (philosophy) , graph theory , algebraic graph theory , trajectory , network topology , control (management) , mathematics , artificial intelligence , theoretical computer science , algorithm , mathematical analysis , philosophy , physics , epistemology , quantum mechanics , combinatorics , astronomy , operating system
Summary This paper addresses the leader‐follower output consensus problem for a class of uncertain nonlinear multiagent systems in a directed communication topology. By employing the backstepping method, the dynamic surface control technique, neutral networks, and the graph theory, a distributed adaptive control scheme is developed recursively for each follower using its own and neighbors' information. The key features of this strategy are that it reduces the computational burden by introducing the dynamic surface control approach and there is no requirement for a priori knowledge about uncertain dynamics of the system. Moreover, in theory, it is proved that the designed control approach can steer the output signals of followers in a directed graph to track the desired trajectory of the leader and guarantee all signals in the closed‐loop system cooperatively semiglobally uniformly ultimately bounded. Furthermore, two examples are included, and the simulation results demonstrate the effectiveness of the proposed strategy.