Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems

Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems

We consider the problem of robust simultaneous fault and state estimation for linear uncertain discrete-time systems with unknown faults which affect both the state and the observation matrices. Using transformation of the original system, a new robust proportional integral filter (RPIF) having an e...

Full description

Bibliographic Details
Main Authors: Feten Gannouni, Fayçal Ben Hmida
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2017/9251031
id doaj-7a058eb8d981484892f66524c04677df
record_format Article
spelling doaj-7a058eb8d981484892f66524c04677df2020-11-24T22:15:21ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472017-01-01201710.1155/2017/92510319251031Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain SystemsFeten Gannouni0Fayçal Ben Hmida1National Higher School of Engineering of Tunis (ENSIT), Laboratoire d’Ingenierie des Systèmes Industriels et des Energies Renouvelables (LISIER), University of Tunis, 5 Taha Hussein Street, BP 56, 1008 Tunis, TunisiaNational Higher School of Engineering of Tunis (ENSIT), Laboratoire d’Ingenierie des Systèmes Industriels et des Energies Renouvelables (LISIER), University of Tunis, 5 Taha Hussein Street, BP 56, 1008 Tunis, TunisiaWe consider the problem of robust simultaneous fault and state estimation for linear uncertain discrete-time systems with unknown faults which affect both the state and the observation matrices. Using transformation of the original system, a new robust proportional integral filter (RPIF) having an error variance with an optimized guaranteed upper bound for any allowed uncertainty is proposed to improve robust estimation of unknown time-varying faults and to improve robustness against uncertainties. In this study, the minimization problem of the upper bound of the estimation error variance is formulated as a convex optimization problem subject to linear matrix inequalities (LMI) for all admissible uncertainties. The proportional and the integral gains are optimally chosen by solving the convex optimization problem. Simulation results are given in order to illustrate the performance of the proposed filter, in particular to solve the problem of joint fault and state estimation.http://dx.doi.org/10.1155/2017/9251031
collection DOAJ
language English
format Article
sources DOAJ
author Feten Gannouni
Fayçal Ben Hmida
spellingShingle Feten Gannouni
Fayçal Ben Hmida
Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems
Mathematical Problems in Engineering
author_facet Feten Gannouni
Fayçal Ben Hmida
author_sort Feten Gannouni
title Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems
title_short Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems
title_full Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems
title_fullStr Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems
title_full_unstemmed Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems
title_sort simultaneous robust fault and state estimation for linear discrete-time uncertain systems
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2017-01-01
description We consider the problem of robust simultaneous fault and state estimation for linear uncertain discrete-time systems with unknown faults which affect both the state and the observation matrices. Using transformation of the original system, a new robust proportional integral filter (RPIF) having an error variance with an optimized guaranteed upper bound for any allowed uncertainty is proposed to improve robust estimation of unknown time-varying faults and to improve robustness against uncertainties. In this study, the minimization problem of the upper bound of the estimation error variance is formulated as a convex optimization problem subject to linear matrix inequalities (LMI) for all admissible uncertainties. The proportional and the integral gains are optimally chosen by solving the convex optimization problem. Simulation results are given in order to illustrate the performance of the proposed filter, in particular to solve the problem of joint fault and state estimation.
url http://dx.doi.org/10.1155/2017/9251031
work_keys_str_mv AT fetengannouni simultaneousrobustfaultandstateestimationforlineardiscretetimeuncertainsystems
AT faycalbenhmida simultaneousrobustfaultandstateestimationforlineardiscretetimeuncertainsystems
_version_ 1725794830502592512

Similar Items