Robust identification of systems with both bias and variance disturbances
type: Item
instance of: scholarly article
title: Robust identification of systems with both bias and variance disturbances
zbMATH Open document ID: 0817.93070
author: Lei Guo
author: Chen Wei
published in: Chinese Science Bulletin
publication date: 1995-01-19T00:00:00Z
review text: The authors present some bounds on the estimation errors for transfer function estimates of discrete-time SISO systems with both random and deterministic disturbances. The random disturbance referred to as ``variance disturbance'' is a martingale difference sequence while the bounded deterministic sequence is called ``bias disturbance''. The system input is an adapted ARMA process. The main result of the note states that the bias disturbance does not upset the \(L^ \infty\) strong consistency of the identification algorithm based on the least-square estimation of discrete transfer function coefficients. Moreover, the authors adopt an input normal realization truncation for model reduction and give bounds on the approximation error for the reduced order transfer function. The estimated transfer function is strongly consistent under some mild conditions on the decaying rate of its coefficients.
Mathematics Subject Classification ID: 93E12
Mathematics Subject Classification ID: 93E24
Mathematics Subject Classification ID: 93C55
Mathematics Subject Classification ID: 93A30
zbMATH DE Number: 713517
zbMATH Keywords: robust identification
zbMATH Keywords: discrete-time
zbMATH Keywords: disturbances
zbMATH Keywords: \(L^ \infty\) strong consistency
zbMATH Keywords: least-square estimation
zbMATH Keywords: reduced order transfer function
zbMATH Keywords: random disturbances
reviewed by: Andrzej Świerniak
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 713517