Bond Graph Model Based on Structural Diagnosability and Recoverability Analysis: Application to Intelligent Autonomous Vehicles

2012 ◽  
Vol 61 (3) ◽  
pp. 986-997 ◽  
Author(s):  
Rui Loureiro ◽  
Rochdi Merzouki ◽  
Belkacem Ould Bouamama
Keyword(s):  
Autonomous Vehicles ◽  
Graph Model ◽  
Bond Graph ◽  
Model Based ◽  
Analysis Application

Bond graph model-based fault detection using residual sinks

2008 ◽  
Vol 223 (3) ◽  
pp. 337-352 ◽  
Author(s):  
W Borutzky
Keyword(s):  
Fault Detection ◽  
Numerical Computation ◽  
Graph Model ◽  
Numerical Differentiation ◽  
Equation System ◽  
Bond Graph ◽  
Engineering System ◽  
Differential Algebraic Equation ◽  
Symbolic Form ◽  
Model Based

In this paper, residual sinks are used in bond graph model-based quantitative fault detection for the coupling of a model of a faultless process engineering system to a bond graph model of the faulty system. By this way, integral causality can be used as the preferred computational causality in both models. There is no need for numerical differentiation. Furthermore, unknown variables do not need to be eliminated from power continuity equations in order to obtain analytical redundancy relations (ARRs) in symbolic form. Residuals indicating faults are computed numerically as components of a descriptor vector of a differential algebraic equation system derived from the coupled bond graphs. The presented bond graph approach especially aims at models with non-linearities that make it cumbersome or even impossible to derive ARRs from model equations by elimination of unknown variables. For illustration, the approach is applied to a non-controlled as well as to a controlled hydraulic two-tank system. Finally, it is shown that not only the numerical computation of residuals but also the simultaneous numerical computation of their sensitivities with respect to a parameter can be supported by bond graph modelling.

Bond Graph Model Based and Fuzzy Logic For Robust FDI of Mechatronic Systems

2012 ◽  
Vol 45 (20) ◽  
pp. 126-131
Author(s):  
N. Chatti ◽  
A-L. Gehin ◽  
R. Merzouki ◽  
B. Ould Bouamama ◽  
Y. Touati
Keyword(s):  
Fuzzy Logic ◽  
Graph Model ◽  
Bond Graph ◽  
Mechatronic Systems ◽  
Model Based

scholarly journals Autonomous vehicle traction subsystem modeling and diagnosis using BG-PCs

10.29007/qj7v ◽  
2018 ◽  
Author(s):  
Carlos Alonso-González ◽  
Anibal Bregon ◽  
Belarmino Pulido ◽  
Matías Nacusse ◽  
Sergio Junco
Keyword(s):  
Fault Diagnosis ◽  
Autonomous Vehicles ◽  
Health Management ◽  
Autonomous Vehicle ◽  
Graph Model ◽  
Bond Graph ◽  
Efficient Operation ◽  
Brushless Dc Motors ◽  
Brushless Dc ◽  
Maintenance Requirements

Fault diagnosis is an essential part in the Health Management of autonomous vehicles. Within these vehicles the traction subsystem is a critical component, especially in those exploring planetary surfaces. Recent advances in brushless DC motors has raised the interest in new models and control configurations to integrate them in those vehicles due to their low energy consumption high torque/- mass ratio and low maintenance requirements. In this work we develop a full Bond Graph model of this subsystem, including the brushless motor and the control blocks needed for proper and efficient operation. These models will allow us to perform fault diagnosis with Bond Graph Possible Conflicts as the unifying formalism. We derive the Bond Graph-Possible Conflicts of the system, discussing the viability of the proposal.

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