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Title: System identification algorithm for non-uniformly sampled data
Authors: Bekiroglu, Korkut
Lagoa, Constantino
Lanza, Stephanie T.
Sznaier, Mario
Keywords: Non-uniformly Sampled Data
Continuous Time System Identification
DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2017
Source: Bekiroglu, K., Lagoa, C., Lanza, S. T., & Sznaier, M. (2017). System identification algorithm for non-uniformly sampled data. IFAC-PapersOnLine, 50(1), 7296-7301. doi:10.1016/j.ifacol.2017.08.1460
Series/Report no.: IFAC-PapersOnLine
Abstract: Considerable effort has been devoted to the development of algorithms for identification of parsimonious discrete time models from noisy input/output data sets since this facilitates controller design. Several methods, such as nuclear norm minimization, have been used to provide approximate solutions to this non-convex problem. However, even though the field of continuous time system identification is now mature, results on parsimonious model identification of continuous time systems are still very limited. In this paper, an atomic norm minimization method is proposed for this purpose that can handle non-uniformly sampled data without preprocessing. The proposed approach provides an efficient way to use noisy, non-uniformly sampled data to determine a reliable, low-order continuous time model. Numerical performance is illustrated using academic examples and simulated behavioral data from a smoking cessation study.
ISSN: 2405-8963
Rights: © 2017 IFAC (International Federation of Automatic Control). This paper was published in IFAC-PapersOnLine and is made available as an electronic reprint (preprint) with permission of IFAC (International Federation of Automatic Control). The published version is available at: []. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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