DocumentCode
830641
Title
A Chebyshev system approach to optimal input design
Author
Zarrop, Martin B.
Author_Institution
Imperial College of Science and Technology, London, England
Volume
24
Issue
5
fYear
1979
fDate
10/1/1979 12:00:00 AM
Firstpage
687
Lastpage
698
Abstract
This paper considers the problem of generating test signals for estimating
parameters in linear single-input single-output stochastic systems using a frequency domain approach. The input signals are power constrained and are optimal in the sense of maximizing system information where the criterion employed is a scalar function of the inverse Fisher information matrix. Minimal properties of test signals are discussed and a necessary and sufficient condition for local identifiability is proved based on the concept of an input design index. Conditions are sought under which optimality is achieved by test signals whoso design index is the minimum necessary to ensure identifiability. It is shown that the theory of Chebyshev systems (
-systems) furnishes a fruitful approach in which the set of information matrices can be represented as a convex set (moment space) induced in Rpby a
-system. These considerations lead to the concept of canonical and principal spectral representations of test signals with the required minimal properties and to sufficient conditions for the existence of optimal designs of the desired type, placing only weak restrictions on the choice of optimality criterion. A number of examples are presented that illustrate the usefulness of a geometrical approach.
parameters in linear single-input single-output stochastic systems using a frequency domain approach. The input signals are power constrained and are optimal in the sense of maximizing system information where the criterion employed is a scalar function of the inverse Fisher information matrix. Minimal properties of test signals are discussed and a necessary and sufficient condition for local identifiability is proved based on the concept of an input design index. Conditions are sought under which optimality is achieved by test signals whoso design index is the minimum necessary to ensure identifiability. It is shown that the theory of Chebyshev systems (
-systems) furnishes a fruitful approach in which the set of information matrices can be represented as a convex set (moment space) induced in Rpby a
-system. These considerations lead to the concept of canonical and principal spectral representations of test signals with the required minimal properties and to sufficient conditions for the existence of optimal designs of the desired type, placing only weak restrictions on the choice of optimality criterion. A number of examples are presented that illustrate the usefulness of a geometrical approach.Keywords
Chebyshev functions; Linear systems, stochastic; Parameter estimation; Stochastic systems, linear; Chebyshev approximation; Covariance matrix; Helium; Parameter estimation; Power generation; Signal design; Signal generators; Signal processing; Sufficient conditions; System testing;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.1979.1102160
Filename
1102160
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