Open AccessDistributed consensus tracking for non‐linear multi‐agent systems with input saturation: a command filtered backstepping approach
Author(s) -
Cui Guozeng,
Xu Shengyuan,
L. Lewis Frank,
Zhang Baoyong,
Ma Qian
Publication year - 2016
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.2015.0627
Subject(s) - backstepping , control theory (sociology) , bounded function , multi agent system , consensus , computer science , lyapunov function , linear system , directed graph , lyapunov stability , graph , nonlinear system , mathematics , adaptive control , control (management) , algorithm , artificial intelligence , theoretical computer science , mathematical analysis , physics , quantum mechanics
This study deals with the distributed consensus tracking problem for non‐linear multi‐agent systems under a fixed directed graph. The dynamics of the followers are taken as strict‐feedback structures with unknown non‐linearities and input saturation. Neural networks are utilised to identify a certain scalar related to the unknown non‐linear functions, and an auxiliary system is introduced into the control design to compensate the effect of input saturation. By incorporating the command filtered technique into the backstepping design framework, a distributed consensus control scheme is constructed recursively. Using the Lyapunov stability theory, it is proved that all signals in the closed‐loop systems are cooperatively semi‐globally uniformly ultimately bounded and the consensus tracking errors converge to a small neighbourhood of origin by tuning the design parameters. Finally, simulation result demonstrates the effectiveness of the proposed control approach.