Heading Controller for a Fixed Wing UAV with Reduced Control Surfaces Based on ANFIS

In the last decade, there has been a rising interest in cyber physical systems (CPS), both in civil and military use. Together with the popularization and evolution of navigation sensors, as global position system (GPS) and inertial measurement unit (IMU), has triggered researches in control systems that are more suitable to non-linear systems of an airplane in flight. Classic control systems has been used from simplified mathematical model. As dynamic systems may present complex behaviour, new concepts and technologies of advanced control systems needs to be used. In this work is shown a control method that combine the reasoning of fuzzy logic with the learning of neural network. An adaptive neuro-fuzzy inference system is described to control the heading of an unmanned aerial vehicle (UAV) with a delta type fixed wing with reduced control surfaces called elevens. The UAV has an embedded autopilot board with a micro-controller (mcu) capable of real-time data processing and navigation sensors making this platform suitable for autonomous flight.