This survey of model-based fault diagnosis focuses on those methods that are applicable to
aerospace systems. To highlight the characteristics of aerospace models, generic non-linear …

A new algorithm is proposed to deal with the worst-case optimization of black-box functions
evaluated through costly computer simulations. The input variables of these computer …

Reusable liquid-propellant rocket engines (LPREs) imply more demanding robustness
requirements than expendable ones due to their extended capabilities. Therefore, the goal …

The current context of launchers reusability requires the improvement of control algorithms
for their liquid-propellant rocket engines. Their transient phases are generally still performed …

This article describes a new method to perform fault detection and isolation for a closed-loop-
controlled autonomous aircraft. This vehicle is equipped with standard sensors and …

In order to reach satisfactory performance, fault diagnosis methods require the tuning of
internal parameters, usually called hyperparameters. This is generally achieved by …

Being able to accurately estimate rare event probabilities is a challenging issue in order to
improve the reliability of complex systems. Several powerful methods such as importance …

A diagnosis benchmark was developed for the MASCOTTE test bench of ONERA/CNES. It
consists of a CARINS Simulator of the bench, model-based fault diagnosis algorithms and …

The interacting particle system (IPS) is a recent probabilistic model proposed to estimate
rare event probabilities for Markov chains. The principle of IPS is to apply alternatively …

Rocket engines are complex and critical systems mostly relying on simple redlines
strategies for monitoring the main functional parameters. This approach is typical on …