A nonlinear functional approach to LFT model validation*1
Geir Dullerud*, a and Roy Smithb
aFirst author's affiliation: Department,
Organization,
Urbana, IL 61801 USA
bother authors' affiliations, etc.
This is an abstract
for a presentation given at the
1st Conference on Advanced Nanotechnology:
Research, Applications, and Policy
.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
*Corresponding Address:
Geir Dullerud
mechanical an industrial engineering
1206 West Green Street, Urbana, IL 61801 USA
Phone: +1-217-265-5078 Fax: +1-217-244-6534
Email: dullerud@uiuc.edu
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