Adaptive neural network consensus tracking control for uncertain multi-agent systems with predefined accuracy

This paper proposes the consensus tracking control problem for a class of uncertain nonlinear multi-agent systems. By using a group of nonnegative functions, an adaptive neural network controller is addressed based on the technique of backstepping. Compared with existing results about uncertain nonl...

Full description

Saved in:
Bibliographic Details
Published in:Nonlinear dynamics 2020-09, Vol.101 (4), p.2249-2262
Main Authors: Yao, Dajie, Dou, Chunxia, Yue, Dong, Zhao, Nan, Zhang, Tingjun
Format: Article
Language:English
Subjects:
Automotive Engineering
Classical Mechanics
Control
Dynamical Systems
Engineering
Mechanical Engineering
Original Paper
Vibration
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper proposes the consensus tracking control problem for a class of uncertain nonlinear multi-agent systems. By using a group of nonnegative functions, an adaptive neural network controller is addressed based on the technique of backstepping. Compared with existing results about uncertain nonlinear multi-agent systems, the advantage of the proposed scheme is that it can ensure the consensus of multi-agent systems within a given accuracy by using two n th-order continuous differentiable functions. Finally, simulation results confirm the correctness of the proposed scheme.
ISSN:0924-090X
1573-269X
DOI:10.1007/s11071-020-05885-z