DocumentCode
1090802
Title
Estimating model variance in the case of undermodeling
Author
Hjalmarsson, Haåkan ; Ljung, Lennart
Author_Institution
Dept. of Chem. Eng., California Inst. of Technol., Pasadena, CA, USA
Volume
37
Issue
7
fYear
1992
fDate
7/1/1992 12:00:00 AM
Firstpage
1004
Lastpage
1008
Abstract
A reliable quality estimate of a given model is a prerequisite for any reasonable use of the model. The model error consists of two different contributions: the bias error and the random error. In this contribution, it is shown that the size (variance) of the random error can be reliably estimated in the case where a true system description cannot be achieved in the model structure used. This consistent error estimate can differ considerably from the conventionally used variance estimate, which could thus be misleading
Keywords
modelling; parameter estimation; bias error; model variance estimation; parameter estimation; quality estimate; random error; undermodeling; Autocorrelation; Computer aided software engineering; Control system synthesis; Mathematical model; Reduced order systems; Robust control; Robustness; Stochastic processes; System identification; Transfer functions;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/9.148358
Filename
148358
Link To Document