Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/12678
Title: State and parameter joint estimation of linear stochastic systems in presence of faults and non-Gaussian noises
Authors: Stojanović, Vladimir
He, Shuping
Zhang B.
Issue Date: 2020
Abstract: © 2020 John Wiley & Sons, Ltd. Joint estimation of states and time-varying parameters of linear stochastic systems is of practical importance for fault diagnosis and fault tolerant control. The known fact is that measurements have outliers. They can significantly degrade the properties of linearly recursive algorithms, which are designed to work in presence of Gaussian noises. This article proposes two kinds of strategies for joint parameter-state robust estimation of linear stochastic models in presence of all possible faults and non-Gaussian noises. In the form of Theorem, joint robust algorithm for systems with sensor and component faults, as well as the algorithm for systems with parameter faults are proposed. Because of their good features in robust filtering, Masreliez-Martin filter represents a cornerstone for realization of the proposed robust algorithms for joint state-parameter estimation. The good features of proposed robust estimation algorithms, in relation to algorithms based on other widely-used filters, are illustrated by simulation results. On the other side, intensive research in the field of mathematical modeling of pneumatic servo drives has shown that their mathematical models are nonlinear in which a lot of important details cannot be included in the model. Also, it has been well known that the nonlinear model can be approximated by a linear model with time-varying parameters. Due to the abovementioned reasons, it can be assumed that the pneumatic cylinder model is a linear stochastic model with variable parameters. The good practical values of the proposed robust joint algorithm to identification of the pneumatic cylinder are illustrated by experimental results.
URI: https://scidar.kg.ac.rs/handle/123456789/12678
Type: article
DOI: 10.1002/rnc.5131
ISSN: 1049-8923
SCOPUS: 2-s2.0-85089382564
Appears in Collections:Faculty of Mechanical and Civil Engineering, Kraljevo

Page views(s)

478

Downloads(s)

8

Files in This Item:
File Description SizeFormat 
PaperMissing.pdf
  Restricted Access
29.86 kBAdobe PDFThumbnail
View/Open


Items in SCIDAR are protected by copyright, with all rights reserved, unless otherwise indicated.