Realizing LTI models by identifying characteristic parameters using least squares optimization*-Reference-Cited by-同舟云学术

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Realizing LTI models by identifying characteristic parameters using least squares optimization*

Published:2023-06-13 Issue: Volume: Page:
ISSN:
Container-title:2023 European Control Conference (ECC)
language:
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Author:

Nicolai Tim¹,Haring Mark²,Grøtli Esten I.²,Gravdahl Jan T.³,Reger Johann⁴

Affiliation:

1. Fraunhofer Institute for Industrial Mathematics ITWM,Kaiserslautern,Germany,67663

2. SINTEF Digital,Department of Mathmatics and Cybernetics,Trondheim,Norway,N-7037

3. Norwegian University of Science and Technology,Department of Engineering Cybernetics,Trondheim,Norway,N-7491

4. Technische Universität Ilmenau,Control Engineering Group,Ilmenau,Germany,98684

Funder

Elkem

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10178092/10178115/10178224.pdf?arnumber=10178224

Reference26 articles.

1. An overview of subspace identification

2. The role of vector autoregressive modeling in predictor-based subspace identification

3. Non-asymptotic Identification of Linear Dynamical Systems Using Multiple Trajectories;zheng;Systems & Control Letters,2020

4. Non-asymptotic Identification of LTI Systems from a Single Trajectory

5. Constructing the state of random processes with feedback

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