The scientific project of the ToSyMA team aims to design methodological tools capable of guaranteeing fault tolerance, supervision and safety of dynamic cooperative and distributed systems.
The team’s skills focus on diagnosis: fault detection, location and estimation (Fault Detection and Isolation - FDI), design of fault tolerant control laws (Fault Tolerant Control - FTC), design of fault tolerant multi-sensor data fusion methods - Fault Tolerant Fusion (FTF) with integrity monitoring. This involves proposing FDI, FTC and FTF methods for complex distributed dynamic systems by taking into account the interactions between diagnosis, control and multi-sensor data fusion in the presence of faults in order to guarantee an overall level of safety operating of a system. The proposed methods use model-based approaches or without a priori model (data-driven) approaches. In the proposed approaches, the team deals with models with strong non-linearity while keeping as objective the guarantee of a very high level of safety in the operation of fault tolerant systems. The research carried out within the team focused on 3 main methodological and theoretical thematic axes and a transversal application axis.
The 3 thematic axes are:
• Diagnosis and fault tolerant control of systems;
• Monitoring and fault tolerant multi-sensor data fusion;
• Cyber-security and operational safety.
The transversal application axis concerns:
• Fault tolerant multi-vehicle/robot autonomous systems.
Maan El Badaoui El Najjar
Surveillance des réseaux embarqués des véhicules autonomes : une approche conjointe signal et système
Méthodes de fusion multi-capteurs tolérantes aux défauts. Localisation et caractérisation collaboratives d'un système multi-robots
Localisation coopérative multi-véhicules tolérante aux fautes
Tolérance aux fautes pour la navigation autonome d'un véhicule