Identification for robust H2 deconvolution filtering

doi:10.1016/j.automatica.2010.01.023

Identification for robust H2 deconvolution filtering

2010-03-01

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DOI：10.1016/j.automatica.2010.01.023

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This paper addresses robust deconvolution filtering when the system and noise dynamics are obtained by parametric system identification. Consistent with standard identification methods, the uncertainty in the estimated parameters is represented by an ellipsoidal uncertainty region. Three problems are considered: (1) computation of the worst case H(2) performance of a given deconvolution filter in this uncertainty set; (2) design of a filter which minimizes the worst case H(2) performance in this uncertainty set; (3) input design for the identification experiment, subject to a limited input power budget, such that the filter in (2) gives the smallest possible worst case H(2) performance. It is shown that there are convex relaxations of the optimization problems corresponding to (1) and (2) while the third problem can be treated via iterating between two convex optimization problems. (C) 2010 Elsevier Ltd. All rights reserved.

Keywords:

Deconvolution filtering

System identification

Optimal experiment design

Training signal design

Identification for robust H2 deconvolution filtering

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