Database-driven online safe flight envelope prediction and protection for enhanced aircraft fault tolerance

Database-driven online safe flight envelope prediction and protection for enhanced aircraft fault tolerance

Zhang, Y. (TU Delft Control & Simulation)

Mulder, Max (promotor)
Chu, Q. P. (promotor)
de Visser, C.C. (copromotor)

Delft University of Technology

2019-03-20

Among all the contributors to fatal accidents, in-flight loss of control (LOC-I) remains one of the largest categories, as indicated by statistics of investigations into past civil aircraft accidents. In flight LOC generally refers to accidents in which the flight crew was unable to maintain control of the aircraft in flight, resulting in an unrecoverable deviation from the intended flight path. Compared with other accidents occurrence categories, LOC-I is more challenging to predict and prevent, since it is often the result of a highly complex combination of a wide range of contributing factors. Many in-depth researches into loss of control accidents have been conducted to find out how these events unfold, and to develop effective intervention strategies for preventing LOC.

flight envelope
loss-of-control
database
fault tolerance
machine learning

https://doi.org/10.4233/uuid:70778c5c-3f00-4854-a0fb-98b24c9ed1cb

978-94-028-1418-7

Institutional Repository

doctoral thesis

© 2019 Y. Zhang