OZR2877 - Linear parameter-varying modeling and decentralized fault diagnosis for large sets of interacting subsystem
This project (joint PhD VUB-ULB) aims at developing a model-based decentralized FDI system, for a process made of large sets of interacting subsystems. A relevant example of such a process is a wind farm, where the turbines are interacting with each other through the wake effect. This project addresses the next challenges:
- How to identify Linear Parameter-Varying models [3, 4] for the subsystems from available data (accounting for the dynamic dependence on operating conditions). Continuous-time frequency domain identification [5, 6] will be used since (i) a continuous-time model is closer to the physics than a discrete-time model, and (ii) the modeling can be done in a user defined frequency band.
- How to extend to a decentralized framework the FDI methods currently developed in a centralized way [7, 8], while dealing with the interactions of the subsystems and optimizing the computational load and data exchange. Both additive and multiplicative faults will be considered.