Optimal Experimental Designs with Respect to the Intended Model Application

The purpose of the design of identification experiments is to make the collected data maximally informative with respect to the intended use of the model, subject to constraints that might be at hand. When the true system is replaced by an estimated model, there results a performance degradation tha...

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Bibliographic Details
Published inAutomatica (Oxford) Vol. 22; no. 5; p. 543
Main Authors Gevers, Michel, Ljung, Lennart
Format Journal Article
LanguageEnglish
Published 1986
Subjects
Frequency domain
Identification
Optimization
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ISSN1873-2836
0005-1098
DOI10.1016/0005-1098(86)90064-6

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Summary:The purpose of the design of identification experiments is to make the collected data maximally informative with respect to the intended use of the model, subject to constraints that might be at hand. When the true system is replaced by an estimated model, there results a performance degradation that is due to the error in the transfer function estimates. Using some recent asymptotic expressions for the bias and the variance of the estimated transfer function, it is shown how this performance degradation can be minimized by a proper experiment design. Several applications, where it is beneficial to let the experiment be carried out in closed loop, are highlighted.
ISSN:1873-2836
0005-1098
DOI:10.1016/0005-1098(86)90064-6