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The omnicopter is a small unmanned aerial vehicle capable of executing decoupled translational and rotational motion (six degree of freedom, 6DOF, motion). The development of controllers for various 6DOF controllable multirotors has been much more limited than development for quadrotors, which makes selecting a controller for a 6DOF multirotor difficult. The omnicopter is subject to various uncertainties and disturbances from hardware changes, structural dynamics, and airflow, making adaptive controllers particularly interesting to investigate. The goal of this research is to design and evaluate the performance of various position and attitude controller combinations for the omnicopter, specifically focusing on adaptive controllers. Simulations are first used to compare combinations of three position controllers, PID, model reference adaptive control, augmented model reference adaptive control (aMRAC), and four attitude controllers, PI/feedback linearization (PIFL), augmented model reference adaptive control, backstepping, and adaptive backstepping (aBack). For the simulations, the omnicopter is commanded to point at and track a stationary aim point as it travels along a $C^0$ continuous trajectory and a trajectory that is $C^1$ continuous. The controllers are stressed by random disturbances and the addition of an unaccounted for suspended mass. The augmented model reference adaptive controller for position control paired with the adaptive backstepping controller for attitude control is shown to be the best controller combination for tracking various trajectories while subject to disturbances. Based on the simulation results, the PID/PIFL and aMRAC/aBack controllers are selected to be compared during three different flight tests. The first flight test is on a $C^1$ continuous trajectory while the omnicopter is commanded to point at and track a stationary aim point. The second flight test is a hover with an unmodeled added weight, and the third is a circular trajectory with a broken blade. As with the simulation results, the adaptive controller is shown to yield better performance than the nonadaptive controller for all scenarios, particularly for position tracking. With an added weight or a broken propeller, the adaptive attitude controller struggles to return to level flight, but is capable of maintaining steady flight when the nonadaptive controller tends to fail. Finally, while model reference adaptive controllers are shown to be effective, their nonlinearity can make them difficult to tune and certify via standard certification methods, such as gain and phase margin. A method for using time delay margin estimates, a potential certification metric, to tune the adaptive parameter tuning gain matrix is shown to be useful when applied to an augmented MRAC controller for a quadrotor. / Doctor of Philosophy / The omnicopter is a small unmanned aerial vehicle capable of executing decoupled translational and rotational motion. The development of controllers for these types of vehicles has been limited, making controller selection difficult. The omnicopter is subject to variations in hardware and airflow, making adaptive controllers particularly interesting to investigate. The goal of this research is to design and compare the performance of various position and attitude controller combinations for the omnicopter, specifically focusing on adaptive controllers. Simulations are first used to compare combinations of several position and attitude controllers on various trajectories and disturbances. Simulation results showed that a fully adaptive controller combination produced the best trajectory tracking while subject to disturbances. As with the simulation results, flight tests showed the adaptive controller yields better performance than the nonadaptive controller for all scenarios, particularly for position tracking. Finally, while the adaptive position controller was shown to be effective, it is difficult to tune and certify for widespread use. A method for using time delay margin estimates, a potential certification metric, to tune the adaptive controller is shown to be useful when applied to an adaptive controller for a quadrotor.

The miniature tailsitter is a unique aircraft with inherent advantages over typical unmanned aerial vehicles. With the capabilities of both hover and level flight, these small, portable systems can produce efficient maneuvers for enhanced surveillance and autonomy with little threat to surroundings and the system itself. Such vehicles are accompanied with control challenges due to the two different flight regimes. Problems with the conventional attitude representation arise in estimation and control as the system departs from level flight conditions. Furthermore, changing dynamics and limitations in modeling and sensing give rise to significant attitude control design challenges. Restrictions in computation also result from the limited size and weight capacity of the miniature airframe. In this research, the inherent control challenges discussed above are addressed with a computationally efficient adaptive quaternion control algorithm. A backstepping method for model cancellation and consistent tracking of reference model attitude dynamics is derived. This is used in conjunction with two different algorithms designed for the identification of system parameters. For a metric of baseline performance, gain-scheduled quaternion feedback control is developed. With a regularized data-weighting recursive least-squares parameter estimation algorithm, the adaptive quaternion controller is shown to be better than the baseline method in simulation and hardware results. This method is also shown to produce universal performance for all aircraft with the three conventional control surface actuators (aileron, elevator, and rudder) barring saturation and assuming accurate system identification. Testing of attitude control algorithms requires development in quaternion-based navigational control and attitude estimation. A novel technique for hover north/east position control is derived. Also, altitude tracking in hover, given an inconsistent thrust system, is addressed with an original method of on-line throttle system identification. Means for quaternion-based level flight control are produced from adaptations made to existing techniques employed in the Brigham Young University Multi-Agent Coordination and Control Lab. Also generated are simple trajectories for transitions between flight modes. A method for the estimation of quaternion attitude is developed, which uses multiple sensors combined in a filtering technique similar to the fixed-gain Kalman filter. Simulation and hardware results of these methods are presented for concept validation. A discussion of the development and production of these testing means (a simulation environment and hardware flight test system) is provided. In culmination, a fully autonomous miniature tailsitter system is produced with results demonstrating its various capabilities.