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Optimal input design for system identification using spectral decomposition
Published in Taylor and Francis Ltd.
2018
Volume: 93
   
Issue: 4
Pages: 980 - 992
Abstract
The aim of this paper is to design a band-limited optimal input with power constraints for identifying a linear multi-input multi-output system, with nominal parameter values specified. Using spectral decomposition theorem, the power spectrum is written as φu(jω) = 1/2H(jω)H*(jω). The matrix H(jω) is expressed in terms of a truncated basis for L2([-ωc, ωc]), where ωc is the cut-off frequency. The elements of the Fisher Information Matrix and the power constraints become homogeneous quadratics in basis coefficients. The optimality criterion used are D-optimality, A-optimality, T-optimality and ε-optimality. This optimization problem is not known to be convex. A bi-linear formulation gives a lower bound on the optimum, while an upper bound is obtained through a convex relaxation. These bounds can be computed efficiently. The lower bound is used as a suboptimal solution, its sub-optimality determined by the difference between the bounds. Simulations reveal that the bounds match in many instances, implying global optimality. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
About the journal
JournalData powered by TypesetInternational Journal of Control
PublisherData powered by TypesetTaylor and Francis Ltd.
ISSN00207179
Open AccessNo
Concepts (17)
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    Convex optimization
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    Domain decomposition methods
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    Identification (control systems)
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    Matrix algebra
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    Mimo systems
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    Multiplexing equipment
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    Relaxation processes
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    Religious buildings
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    CONVEX OPTIMISATION
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    LINEAR FORMULATION
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    LINEAR MULTI-INPUT MULTI-OUTPUT SYSTEM
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    OPTIMAL INPUT DESIGN
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    OPTIMALITY CRITERIA
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    Optimization problems
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    SPECTRAL DECOMPOSITION
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    Suboptimal solution
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    Fisher information matrix