|Reference : A Quadratic Programming Framework for Constrained and Robust Jet Engine|
|Parts of books : Contribution to collective works|
|Physical, chemical, mathematical & earth Sciences : Mathematics|
Physical, chemical, mathematical & earth Sciences : Physics
Physical, chemical, mathematical & earth Sciences : Space science, astronomy & astrophysics
Engineering, computing & technology : Aerospace & aeronautics engineering
Engineering, computing & technology : Mechanical engineering
|A Quadratic Programming Framework for Constrained and Robust Jet Engine|
|Borguet, Sébastien [Université de Liège - ULg > Département d'aérospatiale et mécanique > Turbomachines et propulsion aérospatiale >]|
|Léonard, Olivier [Université de Liège - ULg > Département d'aérospatiale et mécanique > Turbomachines et propulsion aérospatiale >]|
|EUCASS Advances in Aerospace Sciences : Propulsion Physics|
|[en] Kalman filters ; jet engine ; Quadratic Programming Framework|
|[en] Kalman filters are largely used in the jet engine community for condition monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the residuals between the model prediction and the measurements are zero-mean, Gaussian random variables. In the case of sensor faults, this assumption does not hold anymore and consequently the diagnosis is spoiled. This contribution presents a recursive estimation algorithm based on a Quadratic Programming formulation which provides robustness against sensor faults and allows constraints on the health parameters to be specified. The improvements in estimation accuracy brought by this new algorithm are illustrated by a series of typical test-cases that may be encountered on current turbofan engines.|
|Researchers ; Professionals ; Students|
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