The application of the canonical correlation concept to the identification of linear state space models
Lecture notes in control and information sciencesPublished 1 January 1988
Bart De Moor, Moonen Marc, Lieven Vandenberghe, Joos Vandewalle
Citations8
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
In this paper, a geometrically inspired algorithm is derived for identification of state space models for multivariable linear time-invariant systems using noisy input-output measurements. The algorithm contains two conceptual steps which allow a robust implementation using SVD techniques: These results are applied to the identification of an industrial plant.
Keywords
Engineering
IEEE Transactions on Automatic ControlStochastic theory of minimal realization
426 Citations1974Hirotugu Akaike
System Identification, Reduced-Order Filtering and Modeling via Canonical Variate Analysis
315 Citations1983Wallace E. Larimore
Linear Algebra and its ApplicationsNew inversion formulas for matrices classified in terms of their distance from Toeplitz matrices
210 Citations1979B. Friedlander, M. Morf +2 more
By introducting a way of characterizing matrices in terms of their “distance” from being Toeplitz, a natural extension of recursive algorithms for finding the inverses of ToEplitz or displacement-type matrices is obtained.
IEEE Transactions on Automatic ControlRealization and reduction of Markovian models from nonstationary data
39 Citations1981Yoram Baram
A Unifying Tool for Comparing Stochastic Realization Algorithms and Model Reduction Techniques
10 Citations1984J. A. Ramos, Erik I. Verriest
