High-performance numerical algorithms and software for subspace-based linear multivariable system identification
type: Item
instance of: scholarly article
title: High-performance numerical algorithms and software for subspace-based linear multivariable system identification
zbMATH Open document ID: 1070.93017
author: Vasile Sima
author: Diana Maria Sima
author: Sabine Van Huffel
published in: Journal of Computational and Applied Mathematics
publication date: 2004-08-10T00:00:00Z
review text: Basic numerical algorithms and a newly developed software are described for subspace-based identification of linear discrete-time state space systems of the form \(x_{k+1}= Ax_k+ Bu_k+ w_k\), \(y_k = Cx_k+ Du_k+ v_k\), where \(x_k\in\mathbb{R}^n\) is the state vector at time \(k\), \(u_k\in\mathbb{R}^m\) is the input vector, \(y_k\in\mathbb{R}^l\) is the output vector, \(A\), \(B\), \(C\) and \(D\) are matrices of corresponding sizes and \(\{w_k\}\), \(\{v_k\}\) are zero-mean, stationary sequences, uncorrelated with \(\{u_k\}\). It is supposed that the system is controllable and observable. A particular model arises when \(w_k= Kv_k\) and \(\{v_k\}\) is a white noise sequence. The standard identification problem is to determine the system order \(n\) and the system matrices using the input and output data sequences. The implementation of two subspace-based algorithms, known as MOESP and N4SID, is considered and an identification toolbox, called SLIDENT, is described. The toolbox incorporates interfaces to the MATLAB and SCILAB environments and is included in the freely available library SLICOT. The main advantages of the SLICOT library include, among others, a greater efficiency and an improved numerical accuracy in comparison with other existing codes.
Mathematics Subject Classification ID: 93B40
Mathematics Subject Classification ID: 93-04
Mathematics Subject Classification ID: 93B30
Mathematics Subject Classification ID: 65K10
zbMATH DE Number: 2085575
zbMATH Keywords: linear multivariable systems
zbMATH Keywords: system identification
zbMATH Keywords: subspace-based identification
zbMATH Keywords: MOESP
zbMATH Keywords: N4SID
zbMATH Keywords: SLIDENT
zbMATH Keywords: MATLAB
zbMATH Keywords: SCILAB
zbMATH Keywords: SLICOT
reviewed by: Mihail M. Konstantinov
describes a project that uses: SLICOT
describes a project that uses: Algorithm 679
describes a project that uses: SMI Toolbox
describes a project that uses: Matlab
describes a project that uses: Scilab
describes a project that uses: LAPACK
describes a project that uses: BLAS
describes a project that uses: System Identification Toolbox
MaRDI profile type: Publication
full work available at URL: j.cam.2003.12.046
OpenAlex ID: W2061068371
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DOI: 10.1016/J.CAM.2003.12.046
description: scientific article; zbMATH DE number 2085575