Massager Louise

Units

Department of control engineering and system analysis

The research activities of the SAAS group are essentially oriented in two directions:
- Supervision and fault diagnosis of technical systems based on mathematical models
- Advanced control of nonlinear dynamic system subject to constraints, with emphasis on reference governor methods
 
The developed methods are applied to a wide range of areas including:
- Electric energy production, distribution and storage
- Mechatronics (UAVs and robotics)
- Industrial processes

Projetcs

SPACE4RELAUNCH -HEALTH MONITORING OF ELECTROMECHANICAL ACTUATORS FOR REUSABLE LAUNCHERS

Due to the expensive nature of rockets, a major challenge consists in reducing their costs. Launchers in particular are quite expensive and the majority is expendable. Market competition brought aerospace enterprises to search for new ways to cut prices, notably by reusing their launch systems. During each stage of ascension, specific boosters constituting the rocket are decoupled, generally left to fall into the sea. One of the reason why launchers are not reused comes down to the lack of knowledge on the health status of their components, including their actuators. The latter typically serve to orientate the nozzle for propulsion. In case of reusable launchers, additional electromechanical actuators (EMAs) can be included to control stabilizing fins and to deploy legs during descent.

The project aims at developing a health monitoring system for high performance electromechanical actuators to be used for reusable launchers. It is part of a WIN4EXCELLENCE programme involving 30 PhD students and dealing with innovative tools for earth observation and reusable launchers. An hybrid fault diagnosis approach is considered for detecting both electrical and mechanical faults, combining a physical model with data-driven techniques. This methodology will require data on both healthy and faulty EMAs. To produce synthetic data on faulty scenarios, the first step consists in establishing a physical-based simulation of the EMA’s health status. The second step is about realising the fault diagnosis. System states will be evaluated through an observer, potentially a Gaussian process.