Model validation for structured uncertainty models

Sundeep Rangan, Kameshwar Poolla

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

Abstract

Model validation concerns the problem of determining if an observed data record is consistent with a given model with prescribed uncertainty bounds. In this paper, we consider time-domain and frequency-domain validation of linear fractional transformation (LFT) uncertainty models with multiple uncertainty blocks. These structured uncertainty models serve as the basic model for H and μ-synthesis robust control design. For these uncertainty models, we propose a computationally efficient approximate validation method based on a convex weighted optimization and H filtering. A simple numerical example is presented.

Original languageEnglish (US)
Title of host publicationProceedings of the 1998 American Control Conference, ACC 1998
Pages629-633
Number of pages5
DOIs
StatePublished - 1998
Event1998 American Control Conference, ACC 1998 - Philadelphia, PA, United States
Duration: Jun 24 1998Jun 26 1998

Publication series

NameProceedings of the American Control Conference
Volume1
ISSN (Print)0743-1619

Other

Other1998 American Control Conference, ACC 1998
CountryUnited States
CityPhiladelphia, PA
Period6/24/986/26/98

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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