Correlation Techniques To Determine Model Form In Robust Nonlinear System Realization/Identification

Item

Title
Correlation Techniques To Determine Model Form In Robust Nonlinear System Realization/Identification
Report Number
WL-TR-91-3078 Volume III, p. GCB-1 thru GCB-17
Creator
Stry, Greselda I.
Mook, D. Joseph
Corporate Author
Department of Mechanical and Aerospace Engineering, State University of New York at Buffalo
Date
1991
Date Issued
1991-08
Extent
17
Identifier
ADA241313
Format
1 online resource
Abstract
The fundamental challenge in identification of nonlinear dynamic systems is determining the appropriate form of the model. A robust technique is presented in this paper which essentially eliminates this problem for many applications. The technique is based on the Minimum Model Error (MME) optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature of the current work is the ability to identify nonlinear dynamic systems without prior assumptions regarding the form of the nonlinearities, in contrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. Model form is determined via statistical correlation of the MME optimal state estimates with the MME optimal model error estimates. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.
Description
The fundamental challenge in identification of nonlinear dynamic systems is determining the appropriate form of the model. A robust technique is presented in this paper which essentially eliminates this problem for many applications. The technique is based on the Minimum Model Error (MME) optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature of the current work is the ability to identify nonlinear dynamic systems without prior assumptions regarding the form of the nonlinearities, in contrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. Model form is determined via statistical correlation of the MME optimal state estimates with the MME optimal model error estimates. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.
Distribution Classification
1
Distribution Conflict
No
DTIC Record Exists
No
Illinois Tech Related
No
Photo Quality
Not needed
Report Availability
Full text available
Type
article
Is Part Of
Proceedings of Damping '91: 13-15 February 1991 San Diego, California (GCA-1 through JCB-17)
Media
ArticleGCB

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Items with "Has Part: Correlation Techniques To Determine Model Form In Robust Nonlinear System Realization/Identification"
Title Class
Proceedings of Damping '91: 13-15 February 1991 San Diego, California (GCA-1 through JCB-17)