A nonlinear functional approach to LFT model validation

Geir E Dullerud, Roy Smith

Research output: Contribution to journalArticle

Abstract

Model validation provides a useful means of assessing the ability of a model to account for a specific experimental observation, and has application to modeling, identification and fault detection. In this paper, we consider a new approach to the model validation problem by deploying quadratic functionals, and more generally nonlinear functionals, to specify noise and dynamical perturbation sets. Specifically, we consider a general linear fractional transformation framework for the model structure, and use constraints involving nonlinear functional inequalities to specify model non-linearities and unknown perturbations, and characteristics of noise and disturbance signals. Sufficient conditions for invalidation of such models are provided in terms of semidefinite programming problems.

Original languageEnglish (US)
Pages (from-to)1-11
Number of pages11
JournalSystems and Control Letters
Volume47
Issue number1
DOIs
StatePublished - Sep 16 2002

Keywords

  • Model validation
  • Multinomial functionals
  • Quadratic constraints
  • Semidefinite programming

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)
  • Mechanical Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'A nonlinear functional approach to LFT model validation'. Together they form a unique fingerprint.

  • Cite this