Journal ArticleDOI
Subspace Identification and ARX Modeling
TLDR
In this article, a high-order ARX model is used to obtain initial estimates of certain Markov parameters, which are then used to restructure the data model used for subspace identification to facilitate the estimation of the state sequence.About:
This article is published in IFAC Proceedings Volumes.The article was published on 2003-09-01. It has received 176 citations till now. The article focuses on the topics: Subspace topology & Markov chain.read more
Citations
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Journal ArticleDOI
An overview of subspace identification
TL;DR: This paper provides an overview of the state of the art of subspace identification methods for both open-loop and closed-loop systems.
Journal ArticleDOI
The role of vector autoregressive modeling in predictor-based subspace identification
TL;DR: The results of this paper provide a unifying framework under which all these algorithms can be viewed and the link with VARX modeling have important implications as to computational complexity is concerned, leading to very computationally attractive implementations.
Journal ArticleDOI
Consistency analysis of some closed-loop subspace identification methods
Alessandro Chiuso,Giorgio Picci +1 more
TL;DR: This work studies statistical consistency of two recently proposed subspace identification algorithms for closed-loop systems and shows that both algorithms are biased due to an unavoidable mishandling of initial conditions which occurs in closed- loop identification.
Journal ArticleDOI
Closed-loop subspace identification methods: an overview
TL;DR: An overview of closed-loop subspace identification methods found in the recent literature and some of the key algorithms that can be shown to have a common origin in autoregressive modelling are highlighted.
Journal ArticleDOI
Sensor fault detection and isolation for wind turbines based on subspace identification and Kalman filter techniques
TL;DR: In this paper, the root moment sensor fault detection and isolation issue for three-bladed wind turbines with horizontal axis is investigated based on the residuals generated by dual Kalman filters.
References
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Book
System Identification: Theory for the User
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Book
Subspace Identification for Linear Systems: Theory - Implementation - Applications
Peter Van Overschee,Bart De Moor +1 more
TL;DR: This book focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finitedimensional dynamical systems, which allow for a fast, straightforward and accurate determination of linear multivariable models from measured inputoutput data.
Journal ArticleDOI
Identification of the deterministic part of MIMO state space models given in innovations form from input-output data
TL;DR: Two algorithms to identify a linear, time-invariant, finite dimensional state space model from input-output data and a special case of the recently developed Multivariable Output-Error State Space (MOESP) class of algorithms based on instrumental variables are described.
Journal ArticleDOI
Closed-loop identification revisited
Urban Forssell,Lennart Ljung +1 more
TL;DR: A new projection approach to closed-loop identification with the advantage of allowing approximation of the open-loop dynamics in a given, and user-chosen frequency domain norm, even in the case of an unknown, nonlinear regulator.
Proceedings ArticleDOI
System Identification, Reduced-Order Filtering and Modeling via Canonical Variate Analysis
TL;DR: In this article, the canonical variate method is extended to approximately solve this problem and give a near optimal reduced-order state space model, which is related to the Hankel norm approximation method.