Decentralized adaptive output feedback control via input/output inversion

Author

Hovakimyan, Naira ; Lavretsky, Eugene ; Calise, Anthony J. ; Sattigeri, Ramachandra

Author_Institution

Dept. of Autom. & Eng., Virginia Tech, Blacksburg, VA, USA

Volume

2

fYear

2003

fDate

9-12 Dec. 2003

Firstpage

1699

Abstract

A decentralized adaptive output feedback control design is proposed for large-scale interconnected systems. It is assumed that all the controllers share prior information about the system reference models. Based on that information, a linearly parameterized neural network is introduced for each subsystem to partially cancel the effect of the interconnections on the tracking performance. Boundedness of error signals is shown through Lyapunov´s direct method.

Keywords

Lyapunov methods; adaptive control; control system synthesis; decentralised control; feedback; interconnected systems; neural nets; Lyapunov direct method; adaptive control; controllers; decentralized control; error signal boundedness; input inversion; large-scale interconnected systems; linearly parameterized neural network; output feedback control; output inversion; tracking performance; Adaptive control; Communication system control; Control design; Control systems; Large-scale systems; Network synthesis; Neural networks; Output feedback; Programmable control; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2003. Proceedings. 42nd IEEE Conference on

ISSN

0191-2216

Print_ISBN

0-7803-7924-1

Type

conf

DOI

10.1109/CDC.2003.1272857

Filename

1272857