UAVs have become an essential tool in many market segments, particularly the military where critical intelligence can be gathered by them. A tailsitter aircraft is a platform whose purpose is to efficiently merge the range and endurance of fixed-wing aircraft with the VTOL capabilities of rotorcraft and is of significant value in applications where launch and recovery area is limited or the use of launch and recovery equipment is not desirable. Developing autopilot software for a tailsitter UAV is unique in that the aircraft must be autonomously controlled over a much wider range of attitudes than conventional UAVs. Assumptions made in conventional estimation and control algorithms are not valid for tailsitter aircraft because of routine operation around gimbal lock. Quaternions are generally employed to overcome the limitations Euler angles; however, adapting the attitude representation to work at a full range of attitudes is only part of the solution. Kalman filter measurement updates and control algorithms must also work at any orientation. This research presents several methods of incorporating a magnetometer measurement into an extended Kalman filter. One method combines magnetometer and accelerometer sensor data using the solution to Wahba's problem to calculate an overall attitude measurement. Other methods correct only heading error and include using two sets of Euler angles to update the estimate, using quaternions to determine heading error and Euler angles to update the estimate, and using only quaternions to update the estimate. Quaternion feedback attitude control is widely used in tailsitter aircraft. This research also shows that in spite of its effective use in spacecraft, using the attitude error calculated via quaternions to drive flight control surfaces may not be optimal for tailsitters. It is shown that during hover when heading error is present, quaternion feedback can cause undesired behavior, particularly when the heading error is large. An alternative method for calculating attitude error called resolved tilt-twist is validated, improved, and shown to perform better than quaternion feedback. Algorithms are implemented on a commercially available autopilot and validation is performed using hardware in loop simulation. A custom interface is used to receive autopilot commands and send the autopilot simulated sensor information. The final topic covered deals with the tailsitter hovering in wind. As the tailsitter hovers, wind can cause the tailsitter to turn such that the wind is perpendicular to the wings. Wind tunnel data is taken and analyzed to explain this behavior.
College and Department
Ira A. Fulton College of Engineering and Technology; Mechanical Engineering
BYU ScholarsArchive Citation
Beach, Jason M., "Development of Tailsitter Hover Estimation and Control" (2014). Theses and Dissertations. 3820.
tailsitter, unmanned air vehicle, magnetometer, Kalman filter, estimation, quaternion, attitude control