Paper Info
Title
Consensus control of higher-order nonlinear multi-agent systems with unknown control directions
Abstract
In this paper, we investigate the distributed consensus control of higher-order nonlinear multi-agent systems under directed graphs. We consider two cases: (i) multi-agents with unknown identical control directions and uncertain dynamics, and (ii) multi-agents with unknown nonidentical control directions and known dynamics. In the first case, a distributed adaptive control protocol is designed based on neural networks (NN) and Nussbaum functions. In the second case, a distributed nonlinear PI control protocol is proposed. It is proved via Lyapunov stability analysis that our developed protocols can ensure the asymptotical convergence of the consensus errors and global uniform boundedness of all the closed-loop signals. Theoretical results are verified by numerical simulations.
Year
DOI
Venue
2019
10.1016/j.neucom.2019.05.074
Neurocomputing
Keywords
Field
DocType
Neural networks,Unknown control directions,Higher-order systems,Distributed control
Convergence (routing),Consensus,Nonlinear system,Control theory,Uniform boundedness,Lyapunov stability,Directed graph,Artificial intelligence,Adaptive control,Artificial neural network,Machine learning,Mathematics
Journal
Volume
ISSN
Citations 
359
0925-2312
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Zhihua Zhang119845.87
Chaoli Wang25811.04
Xuan Cai3225.77