TY - JOUR
T1 - Extending the Best Linear Approximation Framework to the Process Noise Case
AU - Schoukens, Maarten
AU - Pintelon, Rik
AU - Dobrowiecki, Tadeusz
AU - Schoukens, Joannes
N1 - Funding Information:
Manuscript received July 6, 2018; revised July 8, 2018 and February 5, 2019; accepted May 26, 2019. Date of publication June 14, 2019; date of current version March 27, 2020. The work of M. Schoukens was supported by the European Union\u2019s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Fellowship under Grant 798627. The work of T. P. Dobrowiecki supported by BME FIKP-MI/SC. This work was supported in part by the Fund for Scientific Research (FWO Vlaanderen), and in part by the Flemish Government (Methusalem Grant METH1) Recommended by Associate Editor G. Pil-lonetto. (Corresponding author: Maarten Schoukens.) M. Schoukens is with the Eindhoven University of Technology, Control Systems Group, Eindhoven 5600 MB, The Netherlands (e-mail:, [email protected]).
Publisher Copyright:
© 1963-2012 IEEE.
PY - 2020/4/1
Y1 - 2020/4/1
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.
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 -