A nonlinear functional approach to LFT model validation

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Geir Dullerud and Roy Smith

Systems and Control Letters, Volume 47, Issue 1, 16 September 2002, Pages 1-11 DOWNLOAD (full text)

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.

Author Keywords: Model validation; Quadratic constraints; Multinomial functionals; Semidefinite programming