Input fault detection and estimation using PI observer based on the ARX-Laguerre model

This work is dedicated to the synthesis of a new fault detection and identification scheme for the actuator and/or sensor faults modeled as unknown inputs of the system. The novelty of this scheme consists in the synthesis of a new structure of proportional-integral observer (PIO) reformulated from...

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Bibliographic Details
Published in:International journal of advanced manufacturing technology Vol. 90; no. 5-8; pp. 1317 - 1336
Main Authors: Najeh, Tawfik, Ben Njima, Chakib, Garna, Tarek, Ragot, José
Format: Journal Article
Language:English
Published: London Springer London 01.05.2017
Springer Nature B.V
Springer Verlag
Subjects:
Actuators
Automatic
CAE) and Design
Computer simulation
Computer-Aided Engineering (CAD
Engineering
Engineering Sciences
Fault detection
Genetic algorithms
Industrial and Production Engineering
Linear matrix inequalities
Mathematical analysis
Mathematical models
Matrix methods
Mechanical Engineering
Media Management
Original Article
Proportional integral
Synthesis
ARX-Laguerre model
LMI
Pole optimization
Diagnosis
Genetic algorithm
PIO
ISSN:0268-3768, 1433-3015
Online Access:Get full text
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Summary:This work is dedicated to the synthesis of a new fault detection and identification scheme for the actuator and/or sensor faults modeled as unknown inputs of the system. The novelty of this scheme consists in the synthesis of a new structure of proportional-integral observer (PIO) reformulated from the new linear ARX-Laguerre representation with filters on system input and output in order to estimate the unknown inputs presented as faults. The designed observer exploits the input/output measurements to reconstruct the Laguerre filter outputs where the stability and the convergence properties are ensured by using Linear Matrix Inequality. However, a significant reduction of this model is subject to an optimal choice of both Laguerre poles which is achieved by a new proposed identification approach based on a genetic algorithm. The performances of the proposed identification approach and the resulting PIO are tested on numerical simulation and validated on a 2 n d order electrical linear system.
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ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-016-9414-6