Combining Meshless Analysis and Kalman Filters to Estimate Parameters When System Models are Inaccurate

Authors

A. F. Emery, University of Washington
Darrell Pepper, University of Nevada, Las VegasFollow

Document Type

Conference Proceeding

Publication Date

3-13-2011

Publication Title

ASME/JSME 2011 8th Thermal Engineering Joint Conference

Publisher

ASME

First page number:

T10059-1

Last page number:

T10059-8

Abstract

Parameter estimation assumes that the model is an accurate representation of the system being studied and that any deviations are caused by measurement noise. For real experimental data this is often not the case. Clearly, the model will constructed to the highest fidelity by the analyst but when it is deficient, the remedy is not always obvious. One approach is to include a discrepancy function which one hopes will resolve any differences. The paper describes the use of such a function combined with Kalman filtering and meshless FEA.

Keywords

Kalman filtering; Mathematical models; Meshfree methods (Numerical analysis); Systems engineering

Disciplines

Applied Mathematics | Mechanical Engineering | Systems Engineering

Language

English

Comments

Conference held: Honolulu, Hawaii, USA, March 13–17, 2011

Permissions

Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.

Repository Citation

Emery, A. F., Pepper, D. (2011). Combining Meshless Analysis and Kalman Filters to Estimate Parameters When System Models are Inaccurate. ASME/JSME 2011 8th Thermal Engineering Joint Conference T10059-1-T10059-8. ASME.