Distributed consensus control using neural network for a class of nonlinear multi-agent systems

Author

Wen, Guo-Xing ; Chen, C. L Philip

Author_Institution

Dept. of Comput. & Inf. Sci., FST Univ. of Macau, Macau, China

fYear

2012

fDate

14-17 Oct. 2012

Firstpage

2591

Lastpage

2595

Abstract

In this paper, we described a class of nonlinear multi-agent dynamic systems in consensus problem which every agent is multi-dimensional dynamic system. The control objective is expect to find suitable consensus controller for every agent such that 1) guarantee all the signals in the dynamic systems remain bounded. 2) design the consensus controllers for every agent then the average-consensus behavior of the multi-agent systems can be obtained.

Keywords

control system synthesis; distributed control; multi-agent systems; multi-robot systems; neurocontrollers; nonlinear dynamical systems; average-consensus behavior; consensus controller design; consensus problem; control objective; distributed consensus control; multidimensional dynamic system; neural network; nonlinear multiagent dynamic system; Artificial neural networks; Control systems; Multiagent systems; Nonlinear dynamical systems; Vehicle dynamics; consensus control; multi-agent network; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on

Conference_Location

Seoul

Print_ISBN

978-1-4673-1713-9

Electronic_ISBN

978-1-4673-1712-2

Type

conf

DOI

10.1109/ICSMC.2012.6378136

Filename

6378136