A new approach for state estimation of uncertain multiple model with unknown inputs. Application to sensor fault diagnosis

A. Djeddi, Mohamed-Faouzi Harkat, Y. Soufi

Research output: Contribution to journalArticle

Abstract

The present paper proposes a new approach for state estimation of nonlinear systems described by uncertain multiple model with unknown inputs, applied to sensor fault diagnosis. The main idea of the proposed approach is the synthesis of multiple observer for Takagi-Sugeno model with bounded unknown inputs when the known and unknown inputs are affected by uncertainties. The obtained results show the effectiveness of the presented approach which can effectively estimate the state of the considered system involving the used additive terms to overcome the considered uncertainties and sufficient stability conditions are given in terms of Linear Matrix Inequalities (LMIs). The proposed approach is applied successfully to an hydraulic system with three tanks and to detect and isolate sensor faults based on observer bank.

Original languageEnglish
Pages (from-to)537-545
Number of pages9
JournalMediterranean Journal of Measurement and Control
Volume12
Issue number1
Publication statusPublished - 1 Jan 2016
Externally publishedYes

Fingerprint

state estimation
State estimation
Failure analysis
sensors
Sensors
Linear matrix inequalities
hydraulic equipment
Nonlinear systems
Hydraulics
nonlinear systems
synthesis
estimates
Uncertainty

Keywords

  • Fault diagnosis
  • Linear matrix inequality
  • Multiple observer
  • Nonlinear system
  • T-S Fuzzy model
  • Unknown inputs

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Instrumentation

Cite this

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abstract = "The present paper proposes a new approach for state estimation of nonlinear systems described by uncertain multiple model with unknown inputs, applied to sensor fault diagnosis. The main idea of the proposed approach is the synthesis of multiple observer for Takagi-Sugeno model with bounded unknown inputs when the known and unknown inputs are affected by uncertainties. The obtained results show the effectiveness of the presented approach which can effectively estimate the state of the considered system involving the used additive terms to overcome the considered uncertainties and sufficient stability conditions are given in terms of Linear Matrix Inequalities (LMIs). The proposed approach is applied successfully to an hydraulic system with three tanks and to detect and isolate sensor faults based on observer bank.",
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AB - The present paper proposes a new approach for state estimation of nonlinear systems described by uncertain multiple model with unknown inputs, applied to sensor fault diagnosis. The main idea of the proposed approach is the synthesis of multiple observer for Takagi-Sugeno model with bounded unknown inputs when the known and unknown inputs are affected by uncertainties. The obtained results show the effectiveness of the presented approach which can effectively estimate the state of the considered system involving the used additive terms to overcome the considered uncertainties and sufficient stability conditions are given in terms of Linear Matrix Inequalities (LMIs). The proposed approach is applied successfully to an hydraulic system with three tanks and to detect and isolate sensor faults based on observer bank.

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