Thesis (M.S.)--Missouri University of Science and Technology, 2008. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed January 30, 2009) Includes bibliographical references.

This thesis is concerned with developing a control and condition monitoring system for a class of fault tolerant actuators with high levels of redundancy. The High Redundancy Actuator (HRA) is a concept inspired by biomimetics that aims to provide fault tolerance using relatively large numbers of actuation elements which are assembled in parallel and series configurations to form a single actuator. Each actuation element provides a small contribution to the overall force and displacement of the system. Since the capability of each actuation element is small, the effect of faults within the individual element of the overall system is also small. Hence, the HRA will gracefully degrade instead of going from fully functional to total failure in the presence of faults. Previous research on HRA using electromechanical technology has focused on a relatively low number of actuation elements (i.e. 4 elements), which were controlled with multiple loop control methods. The objective of this thesis is to expand upon this, by considering an HRA with a larger number of actuation elements (i.e. 12 elements). First, a mathematical model of a general n-by-m HRA is derived from first principles. This method can be used to represent any size of electromechanical HRA with actuation elements arranged in a matrix form. Then, a mathematical model of a 4-by-3 HRA is obtained from the general n-by-m model and verified experimentally using the HRA test rig. This actuator model is then used as a foundation for the controller design and condition monitoring development. For control design, two classical and control method-based controllers are compared with an H_infinity approach. The objective for the control design is to make the HRA track a position demand signal in both health and faulty conditions. For the classical PI controller design, the first approach uses twelve local controllers (1 per actuator) and the second uses only a single global controller. For the H_infinity control design, a mixed sensitivity functions is used to obtain good tracking performance and robustness to modelling uncertainties. Both of these methods demonstrate good tracking performance, with a slower response in the presence of faults. As expected, the H_infinity control method's robustness to modelling uncertainties, results in a smaller performance degradation in the presence of faults, compared with the classical designs. Unlike previous work, the thesis also makes a novel contribution to the condition monitoring of HRA. The proposed algorithm does not require the use of multiple sensors. The condition monitoring scheme is based on least-squares parameter estimation and fuzzy logic inference. The least-squares parameter estimation estimates the physical parameters of the electromechanical actuator based on input-output data collected from real-time experiments, while the fuzzy logic inference determines the health condition of the actuator based on the estimated physical parameters. Hence, overall, a new approach to both control and monitoring of an HRA is proposed and demonstrated on a twelve elements HRA test rig.

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.