Data model predictive control as a new mathematical framework for simulation and VV&A

Jaenisch, Holger M., Handley, James W., and Hicklen, Michael L. (2006) Data model predictive control as a new mathematical framework for simulation and VV&A. In: Proceedings of SPIE (6229). From: Intelligent Computing: theory and applications IV, 17 April 2006, Orlando, Florida, USA.

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Abstract

This paper presents the mathematical theory and procedure for comparing two simulations analytically. The result is the derivation of two equation models; one for each respective simulation. The derived models are analytically compared to determine: equivalence, consistency, linearity, similarity, and degree of overlap. This yields a unique analytical tool for comparing simulation versions or scenarios for VV&A. Methods as simple as regression can then be used to determine if accreditation is maintained on new simulations or models. The derived analytical functions can themselves be appropriately combined into an adaptive intelligent lookup table (LUT) equivalent model for real-time simulation purposes.

Item ID: 28035
Item Type: Conference Item (Non-Refereed Research Paper)
Keywords: formal analysis; data modeling; VV&A; equivalence; consistency; transfer function modeling; automatic proofing
ISSN: 1996-756X
Date Deposited: 10 Jul 2013 23:54
FoR Codes: 01 MATHEMATICAL SCIENCES > 0102 Applied Mathematics > 010299 Applied Mathematics not elsewhere classified @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970101 Expanding Knowledge in the Mathematical Sciences @ 50%
97 EXPANDING KNOWLEDGE > 970102 Expanding Knowledge in the Physical Sciences @ 50%
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