Title: Identification of positive real models in subspace identification by using regularization
Authors: Goethals, Ivan ×
Van Gestel, Tony
Suykens, Johan
Van Dooren, P
De Moor, Bart #
Issue Date: Oct-2003
Publisher: Ieee-inst electrical electronics engineers inc
Series Title: IEEE Transactions on automatic control vol:48 issue:10 pages:1843-1847
Abstract: In time-domain subspace methods for identifying linear-time invariant dynamical systems, the model matrices are typically estimated from least squares, based on estimated Kalman filter state sequences and the observed outputs and/or inputs. It is well known that for an infinite amount of data, this least squares estimate of the system matrices is unbiased, when the system order is correctly estimated. However, for a finite amount of data, the obtained model may not be positive real, in which case the algorithm is not able to identify a valid stochastic model. In this note, positive realness is imposed by adding a regularization term to a least squares cost function in the subspace identification algorithm. The regularization term is the trace of a matrix which involves the dynamic system matrix and the output matrix.
ISSN: 0018-9286
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Electrical Engineering - miscellaneous
ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
× corresponding author
# (joint) last author

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