PIO Output Fault Diagnosis by ARX-Laguerre Model Applied to 2^{<italic>nd</italic>} Order Electrical System

• Main Authors: Chakib Ben Njima, Tarek Garna
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: ARX-Laguerre model; genetic algorithm; proportional-integral observer
• Online Access: https://ieeexplore.ieee.org/document/9079489/

The novelty of this work 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. This is in order to estimate the unknown outputs presented as faults and to detect the time instant corresponding to the system malfunction. The stability and the convergence properties of the proposed PIO are ensured by using Linear Matrix Inequality. Furthermore an optimal identification of both Laguerre poles is achieved by a genetic algorithm approach where a parametric significant reduction is ensured to guarantee a reduced observer. The performances of the identification approach and the resulting PIO are tested on an experimental 2^nd order electrical system.