Blackboard architecture for an unmanned aerial vehicle controller using fuzzy inference systems
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The objective of this research is to design a controller for low-cost fixed-wing unmanned aerial vehicles (UAV’s) using fuzzy rules and fuzzy inference systems. The control flow in the architecture design process is considered in four levels - Guidance, Navigation, Control & Stability and Communications. The main function of the Fuzzy Logic Control System (FLCS) is to control and stabilize the aircraft while navigating towards different waypoints defined according to the waypoint plan. This idea forms the base for an AI approach to the development of an autopilot unlike the traditional way of using PID controllers for control and navigation.