Decentralized Adaptive Output Feedback Control via Input/Output Inversion

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

Research output: Contribution to journalConference article

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.

Original languageEnglish (US)
Pages (from-to)1699-1704
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume2
StatePublished - Dec 1 2003
Externally publishedYes
Event42nd IEEE Conference on Decision and Control - Maui, HI, United States
Duration: Dec 9 2003Dec 12 2003

Fingerprint

Lyapunov Direct Method
Interconnected Systems
Output Feedback Control
Cancel
Reference Model
Prior Information
Large-scale Systems
Control Design
Interconnection
Decentralized
Feedback control
Large scale systems
Boundedness
Inversion
Subsystem
Linearly
Neural Networks
Neural networks
Controller
Controllers

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Cite this

Decentralized Adaptive Output Feedback Control via Input/Output Inversion. / Hovakimyan, Naira; Lavretsky, Eugene; Calise, Anthony J.; Sattigeri, Ramachandra.

In: Proceedings of the IEEE Conference on Decision and Control, Vol. 2, 01.12.2003, p. 1699-1704.

Research output: Contribution to journalConference article

Hovakimyan, Naira ; Lavretsky, Eugene ; Calise, Anthony J. ; Sattigeri, Ramachandra. / Decentralized Adaptive Output Feedback Control via Input/Output Inversion. In: Proceedings of the IEEE Conference on Decision and Control. 2003 ; Vol. 2. pp. 1699-1704.
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