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Optimal input design for system identification using spectral decomposition

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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… Click to show full abstract

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 . The matrix is expressed in terms of a truncated basis for , where 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 -optimality, -optimality, -optimality and -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.

Keywords: optimality; spectral decomposition; input; using spectral; optimal input; design

Journal Title: International Journal of Control
Year Published: 2020

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