TY - JOUR
T1 - Subspace identification with moment matching
AU - Inoue, Masaki
N1 - Funding Information:
The author acknowledges the associate editor and anonymous reviewers for their valuable time and many constructive comments. The author acknowledges Prof. Shuichi Adachi, Ayaka Matsubayashi, and Yuma Abe for their comments. Masaki Inoue was born in Aichi, Japan, in 1986. He received the M.E. and Ph.D. degrees in engineering from Osaka University in 2009 and 2012, respectively. He served as a Research Fellow of the Japan Society for the Promotion of Science from 2010 to 2012. From 2012 to 2014, He was a Project Researcher of FIRST, Aihara Innovative Mathematical Modelling Project, and also a Doctoral Researcher of the Graduate School of Information Science and Engineering, Tokyo Institute of Technology. Currently, he is an Assistant Professor of the Faculty of Science and Technology, Keio University. His research interests include stability theory of dynamical systems. He received several research awards including the Best Paper Awards from SICE in 2013, 2015, and 2018, from ISCIE in 2014, from IEEJ in 2017, and the Takeda Best Paper Award from SICE in 2018. He is a member of IEEE, SICE, ISCIE, and IEEJ.
Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2019/1
Y1 - 2019/1
N2 - We propose a deterministic identification method that involves a priori information characterized as moments of a transfer function. The moments are expressed in terms of the solution to a Sylvester matrix equation. The Sylvester equation is incorporated with a conventional subspace identification method, and a problem for moment-constrained subspace identification is formulated. Since the identification problem is in a class of nonlinear optimization problems, it cannot be efficiently solved in numerical computation. Application of a change-of-variable technique reduces the problem to least squares optimization, and the solution provides a state-space model that involves the prespecified moments. Finally, the effectiveness of the proposed method is illustrated in numerical simulations.
AB - We propose a deterministic identification method that involves a priori information characterized as moments of a transfer function. The moments are expressed in terms of the solution to a Sylvester matrix equation. The Sylvester equation is incorporated with a conventional subspace identification method, and a problem for moment-constrained subspace identification is formulated. Since the identification problem is in a class of nonlinear optimization problems, it cannot be efficiently solved in numerical computation. Application of a change-of-variable technique reduces the problem to least squares optimization, and the solution provides a state-space model that involves the prespecified moments. Finally, the effectiveness of the proposed method is illustrated in numerical simulations.
KW - Frequency-response characteristics
KW - Least-squares method
KW - Subspace method
KW - System identification
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U2 - 10.1016/j.automatica.2018.10.002
DO - 10.1016/j.automatica.2018.10.002
M3 - Article
AN - SCOPUS:85055736596
SN - 0005-1098
VL - 99
SP - 22
EP - 32
JO - Automatica
JF - Automatica
ER -