A nonlinear functional approach to LFT model validation

Geir E Dullerud, Roy Smith

Research output: Contribution to journalArticlepeer-review


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
Issue number1
StatePublished - Sep 16 2002


  • 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

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