Synchronized tracking control of multi-agent system with limited information

Rongxin Cui, Shuzhi Sam Ge, Beibei Ren

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In this paper, synchronized tracking control is considered for multiple agents with unknown system dynamics, while the desired trajectory is only available to portion of the team members. Using the weighted average of the neighbors' outputs, adaptive neural network (NN) tracking control is designed for each agent. Rigid mathematical proof was provided for the proposed algorithm based on the Lyapunov analysis. It is shown that, under the proposed NN control, the output tracking error of each agent converges to an adjustable neighborhood of the origin. Simulations of synchronized altitude tracking of multiple unmanned helicopters are provided to demonstrate the effectiveness of the approaches presented.

Original languageEnglish
Title of host publication2010 49th IEEE Conference on Decision and Control, CDC 2010
Pages5480-5485
Number of pages6
DOIs
StatePublished - 2010
Event2010 49th IEEE Conference on Decision and Control, CDC 2010 - Atlanta, GA, United States
Duration: Dec 15 2010Dec 17 2010

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Conference

Conference2010 49th IEEE Conference on Decision and Control, CDC 2010
CountryUnited States
CityAtlanta, GA
Period12/15/1012/17/10

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