A novel approach to model determination using the minimum model error estimation

The purpose of this paper is to present an algorithm for the combination of a proven nonlinear system identification technique, the minimum model error estimation algorithm (MME) with an analysis of variance (ANOVA) correlation routine where a forward stepwise procedure is implemented. The analysis...

Full description

Saved in:
Bibliographic Details
Published in2005 American Control Conference; Portland, OR; USA; 8-10 June 2005 pp. 5046 - 5051 vol. 7
Main Authors Kolodziej, J.R., Mook, D.J.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Aerodynamics
Aerospace engineering
Aerospace industry
Analysis of variance
Biological system modeling
Equations
Error analysis
Fuel cells
State estimation
Time measurement
Online AccessGet full text

Cover

More Information
Summary:The purpose of this paper is to present an algorithm for the combination of a proven nonlinear system identification technique, the minimum model error estimation algorithm (MME) with an analysis of variance (ANOVA) correlation routine where a forward stepwise procedure is implemented. The analysis of variance approach to model identification is well documented primarily in social science literature but has been sparsely written about for engineering applications. This paper shows a significant improvement in nonlinear model identification when used in conjunction with the MME algorithm.
Bibliography:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:0780390989
9780780390980
9780780390997
0780390997
ISSN:0743-1619
2378-5861
DOI:10.1109/ACC.2005.1470812