טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
M.Sc Thesis
M.Sc StudentOsokin Yuri
SubjectTrajectory Planning for Aircraft Engine-Shutoff
Emergencies
DepartmentDepartment of Electrical Engineering
Supervisors Professor Nahum Shimkin
Dr. Aharon Bar-Gill
Full Thesis textFull thesis text - English Version


Abstract

A significant part of air transportation involves General Aviation (GA) aircraft, often

flown by single pilot - either by Visual Flight Rules or Instrumental Flight Rules. In

recent years technological advances in avionics have reached the GA cockpit - clearing the way for safety enhancements in these flight regimes. Engine cut constitutes a critical emergency situation - requiring location of a nearby safe-to-land strip and an energy efficient gliding path towards it. An automated system that can assist the pilot in these tasks can significantly aid the safe landing of the aircraft in such emergencies.

This research addresses the planning of an energy-optimal trajectory for the aircraft towards a given landing strip, in the presence of obstacles - geographical and manmade.

In an un-thrusted aircraft the energy (or altitude) loss may clearly be a critical factor. Because of this consideration, a dynamical model of the aircraft is adopted for trajectory planning, rather than a kinematic one. Our goal is to derive a fast algorithm that is suitable for on-board use in real time.

We start by formulating a continuous optimal-control problem, and transform it to a discrete one by discretizing the spatial coordinates and the aircraft state variables. To retain the properties of continuous problem, we employ "motion flight primitives" in the discretization scheme, which are pre-defined flight segments. Finally, the discrete problem is solved by an optimal graph search algorithm, thus producing the globally

optimal flight path.

For fast operation, the algorithm needs to store pre-computed primitive flight segments between grid points. We show how these segments can be adjusted to variations in the aeroplane mass. The performance of the algorithm is demonstrated in several test and realistic scenarios.