  Quadcopters can suffer from loss of propellers in mid-flight, thus requiring
a need to have a system that detects single and multiple propeller failures and
an adaptive controller that stabilizes the propeller-deficient quadcopter. This
paper presents reinforcement learning based controllers for quadcopters with 4,
3, and 2 (opposing) functional propellers. The paper also proposes a neural
network based propeller fault detection system to detect propeller loss and
switch to the appropriate controller. The simulation results demonstrate a
stable quadcopter with efficient waypoint tracking for all controllers. The
detection system is able to detect propeller failure in a short time and
stabilize the quadcopter.
