NDLI: Data-driven consensus for non-linear networked multi-agent systems with switching topology and time-varying delays

Content Provider	IET Digital Library
Author	Li, Chang Jiang Liu, Guo Ping
Abstract	This study investigates the output consensus problem for a class of non-linear networked multi-agent systems with switching topology and time-varying delays. To synchronise the outputs of the agents, novel distributed data-driven consensus protocols are proposed, where the reference input is designed to be the time-varying average of the agents' output. To avoid the self-tracking phenomenon, the delayed information is introduced in the protocol. The proposed methods merely depend on the input and output data of the neighbouring agents, without using explicit or implicit information of its mathematical model. Sufficient conditions are derived to guarantee the closed-loop stability and consensus, with the convergence rate obtained. Numerical and practical examples are conducted to demonstrate the effectiveness of the proposed protocols.
Starting Page	1773
Ending Page	1779
Page Count	7
ISSN	17518644
Volume Number	12
e-ISSN	17518652
Issue Number	Issue 12, Aug (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/12/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2017.0847
Journal	IET Control Theory & Applications
Publisher Date	2018-04-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Closed Loop System Closed-loop Stability Combinatorial Mathematics Control System Analysis Control System Synthesis Delay Delayed Information Distributed Control Distributed Data-driven Consensus Protocols Input Multi-agent System Multi-robot System Neighbouring Agent Networked Control System Nonlinear Networked Multiagent System Output Output Consensus Problem Output Data Stability Stability in Control Theory Synthesis Method Time Varying System Time-varying Average Time-varying Delay Topology
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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