Updating the Air Traffic Control system with new algorithms, automation, and decision
making tools is an important problem, yet the transportation needs in the United States today
present challenges that are not answered by the kinds of control systems that have been built
in the past. First, aircraft today are equipped with accurate sensors, wireless datalink for
communication, and fast onboard computers, giving the Air Traffic Control system a set of sensory
and computational resources that are distributed throughout the airspace. Second, there is no mechanism
for the air traffic system to support the integration of autonomous pilotless aircraft, known as Unmanned
Aerial Vehicles (UAVs). A burgeoning industry, these aircraft are used in situations in which it is
too dull, or too dangerous, for piloted aircraft. Third, there are strong economic drivers to
bring in new, efficient methods for embedded software design for transportation systems,
which enable safety critical system verification and validation in a cost effective way.
To address these needs in air transportation, new kinds of control algorithms for automated decision
making are needed. They will demand new ways of modeling large scale systems. They will require
strict guarantees of safety and efficiency. The technological focus of the research in my lab is a new
kind of mathematical model, known as a hybrid system, which combines discrete state and continuous
state dynamics. We have developed new control algorithms and software, to both design controllers for
hybrid systems that can guarantee system safety, and to optimize system performance. In this
talk, I will present some of these algorithms, and give examples of how they have been applied to
problems in Air Traffic Control.
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