Fuzzy Logic based Flight Control of a Drone
Project Background: The usage of Drones has increased substantially in recent years. There are many impactful commercial applications such as search & rescue, cargo delivery, agriculture, traffic monitoring, railway surveillance, as depicted in Figure 1 which illustrates NASA’s Collaborative UAS Traffic Management (UTM) System. Drones need to have a Flight Control system integrated into the avionics package onboard the flight platform. The Flight Control system, regarded as the brain of the aircraft as it is responsible for the movement of the drone in the 3D space, is comprised of a circuit board as well as a range of sensors that detect movement of the drone, and user commands “telling” it where to fly. Based on the user commands and sensory data, the Flight Controller provides instructions regarding the speed of the motors (4 in a quadcopter drone) which in turn will cause the drone to maneuver as desired. In addition to the hardware, a flight control system also requires software which maps the inputs collected to motor commands. There are many approaches to designing the flight control algorithm including conventional PID control and the bio-inspired fuzzy logic control.
Research Tasks Proposed: (1) Acquiring an understanding of a flight control system (hardware and software) of an existing quadcopter; (2) Conventional (PID) and Fuzzy Logic controllers and MATLAB implementation/simulation; (3) Learning to fly a quadcopter in UAV MASTER Lab flying arena; (4) Cross-discipline collaboration skills: presentation, writing skills; (5) Potential for research publications and presentations at the local and national levels.
Research Location: This research project will be completed in the UAV MASTER Lab located at the Science Building in the Victory Parkway campus.
Professor, CEAS - Aerospace Eng & Eng Mechanics
745 Baldwin Hall