Unmanned Aerial Vehicles are more and more used in various fields. Many of the Flight Missions they execute are remote-controlled by human operators. Their application range could be greatly extended if unsupervised computer-controlled Flight Missions were possible. To reach the goal of being able to run unsupervised Flight Missions, many hurdles are yet to be cleared. One of the difficult tasks is to provide a control mechanism that is capable of reacting to environmental changes, such as bad weather, unexpected obstacles or system failures. To get closer to the goal of unsupervised Flight Missions, existing Expert System mechanisms along with other technologies that provide automated sensor data gathering and actor control are explored and the limitations that hold back progress are highlighted. Limited Flight control approaches that use data from different sensors to safely adapt the drone’s behaviour and its mission execution are the main focus of the thesis. Furthermore an Expert-System-based concept and implementation for decisionmaking during Adaptive Flight Missions are presented and evaluated for their remaining limitations.