Adaptive and distributed control of nonlinear and heterogeneous multi-agent systems

Author

Bidram, Ali ; Lewis, Frank L. ; Davoudi, Ali ; Ge, S.S.

Author_Institution

Electr. Eng. Dept., Univ. of Texas at Arlington, Arlington, TX, USA

fYear

2013

fDate

10-13 Dec. 2013

Firstpage

6238

Lastpage

6243

Abstract

The tracking synchronization problem of multi-agent systems with unknown nonlinear and heterogeneous dynamics is studied. A feedback linearization approach is used with neural networks to compensate for the uncertainties caused by the unknown and nonlinear dynamics of agents. Using the Lyapunov theory, an adaptive distributed control scheme is designed, and verified through the secondary voltage control of the practical microgrids.

Keywords

Lyapunov methods; adaptive control; compensation; control system synthesis; distributed parameter systems; distributed power generation; feedback; multi-agent systems; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; synchronisation; uncertain systems; voltage control; Lyapunov theory; adaptive distributed control scheme; feedback linearization approach; heterogeneous multi-agent systems; microgrids; neural networks; nonlinear dynamics; secondary voltage control; tracking synchronization problem; uncertainties compensation; Decentralized control; Microgrids; Multi-agent systems; Nonlinear dynamical systems; Synchronization; Vectors; Voltage control;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on

Conference_Location

Firenze

ISSN

0743-1546

Print_ISBN

978-1-4673-5714-2

Type

conf

DOI

10.1109/CDC.2013.6760875

Filename

6760875