<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This work is part of the diagnostic field of hybrid dynamic systems (HDS) whose objective is to ensure proper operation of industrial facilities. The study is initially oriented to the modelling approach dedicated to hybrid dynamical systems (HDS). The objective is to look for an adequate model encompassing both aspects (continuous and event). Then, fault diagnosis technique is synthesised using artificial intelligence (AI) techniques. The idea is to introduce a hybrid version combining neural networks and fuzzy logic for residual generation and evaluation. The proposed approach is then validated on three tank system. The modelling and diagnosis approaches are developed using MATLAB/Simulink environment.</p>
</abstract>

This work is part of the diagnostic field of hybrid dynamic systems (HDS) whose objective is to ensure proper operation of industrial facilities. The study is initially oriented to the modelling approach dedicated to hybrid dynamical systems (HDS). The objective is to look for an adequate model encompassing both aspects (continuous and event). Then, fault diagnosis technique is synthesised using artificial intelligence (AI) techniques. The idea is to introduce a hybrid version combining neural networks and fuzzy logic for residual generation and evaluation. The proposed approach is then validated on three tank system. The modelling and diagnosis approaches are developed using MATLAB/Simulink environment.

A Neural-Fuzzy Approach for Fault Diagnosis of Hybrid Dynamical Systems: Demonstration on Three-Tank System

Laboratory of Automatic Signal and Image Processing (LARATSI), National School of Engineers of Monastir

Acta Mechanica et Automatica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

This work is part of the diagnostic field of hybrid dynamic systems (HDS) whose objective is to ensure proper operation of industrial facilities. The study is...

A Neural-Fuzzy Approach for Fault Diagnosis of Hybrid Dynamical Systems: Demonstration on Three-Tank System

Online veröffentlicht: 15. Mai 2021

Seitenbereich: 1 - 8

Eingereicht: 22. März 2020

Akzeptiert: 10. März 2021

DOI: https://doi.org/10.2478/ama-2021-0001

Schlüsselwörter
hybrid dynamic systems, modelling, residual generation and evaluation, monitoring, fault diagnosis, neural-fuzzy approach

© 2021 Mohammed Said Achbi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A Neural-Fuzzy Approach for Fault Diagnosis of Hybrid Dynamical Systems: Demonstration on Three-Tank System

Online veröffentlicht: 15. Mai 2021

Seitenbereich: 1 - 8

Eingereicht: 22. März 2020

Akzeptiert: 10. März 2021

DOI: https://doi.org/10.2478/ama-2021-0001

Schlüsselwörterhybrid dynamic systems, modelling, residual generation and evaluation, monitoring, fault diagnosis, neural-fuzzy approach

© 2021 Mohammed Said Achbi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
hybrid dynamic systems, modelling, residual generation and evaluation, monitoring, fault diagnosis, neural-fuzzy approach