Adaptive data based neural network leader-follower control of multi-agent networks

Khoo, Suiyang, Yin, Juliang, Wang, Bin, Zhao, Shengkui and Man, Zhihong 2011, Adaptive data based neural network leader-follower control of multi-agent networks, in IECON 2011 : Proceedings of the 37th Annual Conference on IEEE Industrial Electronics Society, IEEE, Piscataway, N.J., pp. 3924-3929.

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Title Adaptive data based neural network leader-follower control of multi-agent networks
Author(s) Khoo, Suiyang
Yin, Juliang
Wang, Bin
Zhao, Shengkui
Man, Zhihong
Conference name IEEE Industrial Electronics Society Conference (37th : 2011 : Melbourne, Vic.)
Conference location Melbourne, Vic.
Conference dates 7-10 Nov. 2011
Title of proceedings IECON 2011 : Proceedings of the 37th Annual Conference on IEEE Industrial Electronics Society
Editor(s) [unknown]
Publication date 2011
Start page 3924
End page 3929
Publisher IEEE
Place of publication Piscataway, N.J.
Summary In this paper, we propose a data based neural network leader-follower control for multi-agent networks where each agent is described by a class of high-order uncertain nonlinear systems with input perturbation. The control laws are developed using multiple-surface sliding control technique. In particular, novel set of sliding variables are proposed to guarantee leader-follower consensus on the sliding surfaces. Novel switching is proposed to overcome the unavailability of instantaneous control output from the neighbor. By utilizing RBF neural network and Fourier series to approximate the unknown functions, leader-follower consensus can be reached, under the condition that the dynamic equations of all agents are unknown. An O(n) data based algorithm is developed, using only the network’s measurable input/output data to generate the distributed virtual control laws. Simulation results demonstrate the effectiveness of the approach.

ISBN 9781612849720
ISSN 1553-572X
Language eng
Field of Research 090602 Control Systems, Robotics and Automation
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
HERDC collection year 2011
Copyright notice ©2011, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30041767

Document type: Conference Paper
Collection: School of Engineering
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Created: Wed, 25 Jan 2012, 13:24:55 EST by Sui Yang Khoo

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