This paper proposes an autopilot system for a small and light unmanned air vehicle called Kiteplane. The Kiteplane has a large delta-shaped main wing that is easily disturbed by the wind, which was minimized by utilizing trim flight with drift. The proposed control system for autonomous trajectory following with a wind disturbance included fuzzy logic controllers, a speed controller, a wind disturbance attenuation block, and low-level feedback controllers. The system was implemented onboard the aircraft. Experiments were performed to test the performance of the proposed system and the Kiteplane nearly succeeded in following the desired trajectory, under the wind disturbance. Although the path was not followed perfectly, the airplane was able to traverse the waypoints by utilizing a failsafe waypoint updating rule.The literal meaning of autopilot is a device that steers a ship, plane, or spacecraft by itself, without a person. However, the expression “on autopilot” has developed a different meaning. Here are some typical uses of the expression “on autopilot,” In this paper we propose an approach for generating real life data over which we have control of the concept and can generate data exhibiting different types of concept drift. The approach uses a 3-D driving game to produce a data stream of instances describing how to drive around a track. The classification problem is learning the driving technique of the driver, which can be affected by changes in the driving environment causing changes to the concept. The paper gives illustrations of different types of concept drift and how standard concept drift handling techniques can adapt to the concept drift.