Isolating errors in models of complex systems

Author

Maryak, John L. ; Asher, Mark S.

Author_Institution

Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA

Volume

29

Issue

2

fYear

1993

fDate

4/1/1993 12:00:00 AM

Firstpage

452

Lastpage

463

Abstract

One of the steps in creating a mathematical model of a system is to test the model after it has been fully specified, to see whether it is performing adequately. Often, it is found that the model is not performing acceptably (e.g. the model is not giving accurate predictions of the performance of the actual system). The same lack of fidelity can also be observed in established models that had been performing well, indicating a change in the actual system. At this point, it is necessary to diagnose where the problem in the model lies; a process called error isolation. An error isolation technique for detecting the misspecified parameter (or set of parameters) is described. This technique is especially designed for use on state-space models of large-scale systems. The authors report on an example of an application of the methodology to localizing errors in the model of an inertial navigation system

Keywords

Bayes methods; error detection; inertial navigation; large-scale systems; state-space methods; Bayesian priors; complex systems; error detection; error isolation; inertial navigation; large-scale systems; mathematical model; misspecified parameter; state-space models; Context modeling; Economic forecasting; Inertial navigation; Laboratories; Large-scale systems; Mathematical model; Performance evaluation; Physics; Predictive models; System testing;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.210083

Filename

210083