Extending the Best Linear Approximation framework to the process noise case

Maarten Schoukens; Rik M. Pintelon; Tadeusz Dobrowiecki; Johan Schoukens

doi:10.1109/TAC.2019.2923038

Extending the Best Linear Approximation framework to the process noise case

Maarten Schoukens (Corresponding author), Rik M. Pintelon, Tadeusz Dobrowiecki, Johan Schoukens

Research output: Contribution to journal › Article › Academic › peer-review

8 Citations (Scopus)

38 Downloads (Pure)

Abstract

The Best Linear Approximation (BLA) framework has already proven to be a valuable tool to analyze nonlinear systems and to start the nonlinear modeling process. The existing BLA framework is limited to systems with additive (colored) noise at the output. Such a noise framework is a simplified representation of reality. Process noise can play an important role in many real-life applications. This paper generalizes the Best Linear Approximation framework to account also for the process noise, both for the open-loop and the closed-loop setting, and shows that the most important properties of the existing BLA framework remain valid. The impact of the process noise contributions on the robust BLA estimation method is also analyzed.

Original language	English
Article number	8736761
Pages (from-to)	1514-1524
Number of pages	11
Journal	IEEE Transactions on Automatic Control
Volume	65
Issue number	4
DOIs	https://doi.org/10.1109/TAC.2019.2923038
Publication status	Published - Apr 2020

Keywords

Best linear approximation (BLA)
nonlinear systems
process noise
system identification

Access to Document

10.1109/TAC.2019.2923038

08736761Final published version, 1.43 MBLicence: TAVERNE

Cite this

@article{968086e6b6c14ee9970f754ed22736bd,

title = "Extending the Best Linear Approximation framework to the process noise case",

abstract = "The Best Linear Approximation (BLA) framework has already proven to be a valuable tool to analyze nonlinear systems and to start the nonlinear modeling process. The existing BLA framework is limited to systems with additive (colored) noise at the output. Such a noise framework is a simplified representation of reality. Process noise can play an important role in many real-life applications. This paper generalizes the Best Linear Approximation framework to account also for the process noise, both for the open-loop and the closed-loop setting, and shows that the most important properties of the existing BLA framework remain valid. The impact of the process noise contributions on the robust BLA estimation method is also analyzed.",

keywords = "Best linear approximation (BLA), nonlinear systems, process noise, system identification",

author = "Maarten Schoukens and Pintelon, {Rik M.} and Tadeusz Dobrowiecki and Johan Schoukens",

year = "2020",

month = apr,

doi = "10.1109/TAC.2019.2923038",

language = "English",

volume = "65",

pages = "1514--1524",

journal = "IEEE Transactions on Automatic Control",

issn = "0018-9286",

publisher = "Institute of Electrical and Electronics Engineers",

number = "4",

}

TY - JOUR

T1 - Extending the Best Linear Approximation framework to the process noise case

AU - Schoukens, Maarten

AU - Pintelon, Rik M.

AU - Dobrowiecki, Tadeusz

AU - Schoukens, Johan

PY - 2020/4

Y1 - 2020/4

N2 - The Best Linear Approximation (BLA) framework has already proven to be a valuable tool to analyze nonlinear systems and to start the nonlinear modeling process. The existing BLA framework is limited to systems with additive (colored) noise at the output. Such a noise framework is a simplified representation of reality. Process noise can play an important role in many real-life applications. This paper generalizes the Best Linear Approximation framework to account also for the process noise, both for the open-loop and the closed-loop setting, and shows that the most important properties of the existing BLA framework remain valid. The impact of the process noise contributions on the robust BLA estimation method is also analyzed.

AB - The Best Linear Approximation (BLA) framework has already proven to be a valuable tool to analyze nonlinear systems and to start the nonlinear modeling process. The existing BLA framework is limited to systems with additive (colored) noise at the output. Such a noise framework is a simplified representation of reality. Process noise can play an important role in many real-life applications. This paper generalizes the Best Linear Approximation framework to account also for the process noise, both for the open-loop and the closed-loop setting, and shows that the most important properties of the existing BLA framework remain valid. The impact of the process noise contributions on the robust BLA estimation method is also analyzed.

KW - Best linear approximation (BLA)

KW - nonlinear systems

KW - process noise

KW - system identification

UR - http://www.scopus.com/inward/record.url?scp=85082749654&partnerID=8YFLogxK

U2 - 10.1109/TAC.2019.2923038

DO - 10.1109/TAC.2019.2923038

M3 - Article

SN - 0018-9286

VL - 65

SP - 1514

EP - 1524

JO - IEEE Transactions on Automatic Control

JF - IEEE Transactions on Automatic Control

IS - 4

M1 - 8736761

ER -

Extending the Best Linear Approximation framework to the process noise case

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this