Section: Overall Objectives

On-line monitoring issues

Classical model-based diagnosis methodologies appear to be inadequate for complex systems due to the intractable size of the model and the computational complexity of the process. It is especially true when one considers on-line diagnosis or when many interacting components (or agents) make up the system. This is why we focus on decentralized approaches which relies on computing local diagnoses from local models and synchronizing them to get a global view of the current state of the system. The problems we are investigating are the following. Which strategy to select for synchronizing in an optimal way the local diagnoses to keep the efficiency and the completeness of the process? Which kind of communication protocols to use? How to improve the efficiency of the computation by using adequate symbolic representations? How to guarantee an efficient incremental process, in an on-line diagnosis context where observations are incrementally collected?

More recently, we enlarge our interest and consider in the same view both monitoring, deficiency detection, diagnosis and the consequent system adaptation or repair. We extended diagnosability to self-healability and investigated how to weave diagnosis and repair, to get adaptive systems maintaining a good QoS, even in unexpected, and even abnormal conditions.