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

Holger M. Jaenisch; James W. Handley; Michael L. Hicklen

doi:10.1117/12.666466

9 May 2006 Data model predictive control as a new mathematical framework for simulation and VV&A

Holger M. Jaenisch, James W. Handley, Michael L. Hicklen

Proceedings Volume 6229, Intelligent Computing: Theory and Applications IV; 62290U (2006) https://doi.org/10.1117/12.666466
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

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.

Citation Download Citation

Holger M. Jaenisch, James W. Handley, and Michael L. Hicklen "Data model predictive control as a new mathematical framework for simulation and VV&A", Proc. SPIE 6229, Intelligent Computing: Theory and Applications IV, 62290U (9 May 2006); https://doi.org/10.1117/12.666466

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