Numerically reliable identification of fast sampled systems: a novel delta-domain data-dependent orthonormal polynomial approach

R.J. Voorhoeve; Tom Oomen

Numerically reliable identification of fast sampled systems: a novel delta-domain data-dependent orthonormal polynomial approach

R.J. Voorhoeve, Tom Oomen

Control Systems Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Abstract— The practical utility of system identification algorithms is often limited by the reliability of their implementation in finite precision arithmetic. The aim of this paper is to develop a method for the numerically reliable identification of fast sampled systems. In this paper, a data-dependent orthonormal polynomial approach is developed for systems parametrized in
the δ-domain. This effectively addresses both the numerical conditioning issues encountered in frequency-domain system identification and the inherent numerical round-off problems of fast-sampled systems in the common Z-domain description. Superiority of the proposed approach is shown in an example.

Original language	English
Title of host publication	Proceedings of the 57th Conference on Decision and Control (CDC)
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	1433-1438
Number of pages	6
ISBN (Electronic)	978-1-5386-1394-8
Publication status	Published - 2018
Event	57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States Duration: 17 Dec 2018 → 19 Dec 2018 Conference number: 57

Conference

Conference	57th IEEE Conference on Decision and Control, CDC 2018
Abbreviated title	CDC 2018
Country/Territory	United States
City	Miami
Period	17/12/18 → 19/12/18

Cite this

@inproceedings{6fd7981a5efa4680befe659b5ebbf171,

title = "Numerically reliable identification of fast sampled systems: a novel delta-domain data-dependent orthonormal polynomial approach",

abstract = "Abstract— The practical utility of system identification algorithms is often limited by the reliability of their implementation in finite precision arithmetic. The aim of this paper is to develop a method for the numerically reliable identification of fast sampled systems. In this paper, a data-dependent orthonormal polynomial approach is developed for systems parametrized inthe δ-domain. This effectively addresses both the numerical conditioning issues encountered in frequency-domain system identification and the inherent numerical round-off problems of fast-sampled systems in the common Z-domain description. Superiority of the proposed approach is shown in an example.",

author = "R.J. Voorhoeve and Tom Oomen",

year = "2018",

language = "English",

pages = "1433--1438",

booktitle = "Proceedings of the 57th Conference on Decision and Control (CDC)",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "57th IEEE Conference on Decision and Control, CDC 2018, CDC 2018 ; Conference date: 17-12-2018 Through 19-12-2018",

}

Voorhoeve, RJ & Oomen, T 2018, Numerically reliable identification of fast sampled systems: a novel delta-domain data-dependent orthonormal polynomial approach. in Proceedings of the 57th Conference on Decision and Control (CDC). Institute of Electrical and Electronics Engineers, Piscataway, pp. 1433-1438, 57th IEEE Conference on Decision and Control, CDC 2018, Miami, Florida, United States, 17/12/18.

Numerically reliable identification of fast sampled systems: a novel delta-domain data-dependent orthonormal polynomial approach. / Voorhoeve, R.J.; Oomen, Tom.
Proceedings of the 57th Conference on Decision and Control (CDC). Piscataway: Institute of Electrical and Electronics Engineers, 2018. p. 1433-1438.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Numerically reliable identification of fast sampled systems

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AU - Voorhoeve, R.J.

AU - Oomen, Tom

N1 - Conference code: 57

PY - 2018

Y1 - 2018

N2 - Abstract— The practical utility of system identification algorithms is often limited by the reliability of their implementation in finite precision arithmetic. The aim of this paper is to develop a method for the numerically reliable identification of fast sampled systems. In this paper, a data-dependent orthonormal polynomial approach is developed for systems parametrized inthe δ-domain. This effectively addresses both the numerical conditioning issues encountered in frequency-domain system identification and the inherent numerical round-off problems of fast-sampled systems in the common Z-domain description. Superiority of the proposed approach is shown in an example.

AB - Abstract— The practical utility of system identification algorithms is often limited by the reliability of their implementation in finite precision arithmetic. The aim of this paper is to develop a method for the numerically reliable identification of fast sampled systems. In this paper, a data-dependent orthonormal polynomial approach is developed for systems parametrized inthe δ-domain. This effectively addresses both the numerical conditioning issues encountered in frequency-domain system identification and the inherent numerical round-off problems of fast-sampled systems in the common Z-domain description. Superiority of the proposed approach is shown in an example.

M3 - Conference contribution

SP - 1433

EP - 1438

BT - Proceedings of the 57th Conference on Decision and Control (CDC)

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

Y2 - 17 December 2018 through 19 December 2018

ER -

Numerically reliable identification of fast sampled systems: a novel delta-domain data-dependent orthonormal polynomial approach

Abstract

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