Title
Distributed Low-Complexity Output Feedback Tracking Control For Nonlinear Multi-Agent Systems With Unmodeled Dynamics And Prescribed Performance
Abstract
This paper investigates the prescribed performance distributed output consensus problem under directed graphs. With the utilisation of a filter, the original system of each follower can be converted into a strict-feedback system. Then, we design a prescribed performance output feedback distributed control protocol by applying the backstepping approach in the converted system. The proposed protocol can guarantee that the consensus tracking error of each agent evolves in predefined decaying bounds to achieve the prescribed performance, that is, the consensus tracking error of each agent converges to a predetermined residual set at a convergence rate no less than a prespecified value and exhibiting a maximum overshoot less than a preassigned constant. Moreover, during the process of consensus, all the signals in the closed-loop system are globally uniformly bounded. A simulation example is given to verify the effectiveness of the proposed control protocol.
Year
DOI
Venue
2019
10.1080/00207721.2019.1597946
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
Keywords
Field
DocType
Distributed control, output feedback, unmodeled dynamics, directed graph, low-complexity control, prescribed performance
Consensus,Residual,Mathematical optimization,Backstepping,Control theory,Overshoot (signal),Directed graph,Uniform boundedness,Rate of convergence,Mathematics,Tracking error
Journal
Volume
Issue
ISSN
50
6
0020-7721
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Xuan Cai1225.77
Chaoli Wang25811.04
Gang Wang301.01
Yu Li47623.69
Luyan Xu501.69
Zhihua Zhang619845.87