Vertical Take-Off and Land (VTOL) Unmanned Air Vehicles (UAVs) possess several desirable characteristics, such as being able to hover and take-off or land in confined areas. One type of VTOL airframe, the tailsitter, has all of these advantages, as well as being able to fly in the more energy-efficient level flight mode. The tailsitter can track trajectories that successfully transition between hover and level flight modes. Three methods for performing transitions are described: a simple controller, a feedback linearization controller, and an adaptive controller. An autopilot navigational state machine with appropriate transitioning between level and hover waypoints is also presented. The simple controller is useful for performing a immediate transition. It is very quick to react and maintains altitude during the maneuver, but tracking is not performed in the lateral direction. The feedback linearization controller and adaptive controller both perform equally well at tracking transition trajectories in lateral and longitudinal directions, but the adaptive controller requires knowledge of far fewer parameters.

The control of systems with uncertain nonlinear dynamics is an important field of control science attracting decades of focus. In this dissertation, four different control strategies are presented using sliding mode control, adaptive control, dynamic compensation, and neural network for a nonlinear aeroelastic system with bounded uncertainties and external disturbance. In Chapter 2, partial state feedback adaptive control designs are proposed for two different aeroelastic systems operating in unsteady flow. In Chapter 3, a continuous robust control design is proposed for a class of single input and single output system with uncertainties. An aeroelastic system with a trailingedge flap as its control input will be considered as the plant for demonstration of effectiveness of the controller. The controller is proved to be robust by both athematical proof and simulation results. In Chapter 3, a robust output feedback control strategy is discussed for the vibration suppression of an aeroelastic system operating in an unsteady incompressible flowfield. The aeroelastic system is actuated using a combination of leading-edge (LE) and trailing-edge (TE) flaps in the presence of different kinds of gust disturbances. In Chapter 5, a neural-network based model-free controller is designed for an aeroelastic system operating at supersonic speed. The controller is shown to be able to effectively asymptotically stabilize the system via both a Lyapunov-based stability proof and numerical simulation results.

This study investigates the use of a Model Reference Adaptive Control (MRAC) direct approach to solve the attitude control problem of an Expendable Launch Vehicle (ELV) during its boost phase of flight. The adaptive autopilot design is based on Lyapunov Stability Theory and provides a useful means for controlling the ELV in the presence of environmental and dynamical uncertainties. Several different basis functions are employed to approximate the nonlinear parametric uncertainties in the system dynamics. The control system is designed so that the desire dresponse to a reference model would be tracked by the closed-loop system. The reference model is obtained via the feedback linearization technique applied to the nonlinear ELV dynamics. The adaptive control method is then applied to a representative ELV longitudinal motion, specifically the 6th flight of Atlas-Centaur launch vehicle (AC-6) in 1965. The simulation results presented are compared to that of the actual AC-6 post-flight trajectory reconstruction. Recommendations are made for modification and future applications of the method for several other ELV dynamics issues, such as control saturation, engine inertia, flexible body dynamics, and sloshing of liquid fuels.

The design optimization of DC-DC converters requires the optimum selection of several parameters to achieve improved efficiency and performance. Some of these parameters are load dependent, line dependent, components dependent, and/or temperature dependent. Designing such parameters for a specific load, input and output, components, and temperature may improve single design point efficiency but will not result in maximum efficiency at different conditions, and will not guarantee improvement at that design point because of the components, temperature, and operating point variations. The ability of digital controllers to perform sophisticated algorithms makes it easy to apply adaptive control, where system parameters can be adaptively adjusted in response to system behavior in order to achieve better performance and stability. The use of adaptive control for power electronics is first applied with the Adaptive Frequency Optimization (AFO) method, which presents an auto-tuning adaptive digital controller with maximum efficiency point tracking to optimize DC-DC converter switching frequency. The AFO controller adjusts the DC-DC converter switching frequency while tracking the converter minimum input power point, under variable operating conditions, to find the optimum switching frequency that will result in minimum total loss and thus the maximum efficiency. Implementing variable switching frequencies in digital controllers introduces two main issues, namely, limit cycle oscillation and system instability. Dynamic Limit Cycle Algorithms (DLCA) is a dynamic technique tailored to improve system stability and to reduce limit cycle oscillation under variable switching frequency operation. The convergence speed and stability of AFO algorithm is further improved by presenting the analysis and design of a digital controller with adaptive auto-tuning algorithm that has a variable step size to track and detect the optimum switching frequency for a DC-DC converter. The Variable-Step-Size (VSS) algorithm is theoretically analyzed and developed based on buck DC-DC converter loss model and directed towered improving the convergence speed and accuracy of AFO adaptive loop by adjusting the converter switching frequency with variable step size. Finally, the efficiency of DC-DC converters is a function of several variables. Optimizing single variable alone may not result in maximum or global efficiency point. The issue of adjusting more than one variable at the same time is addressed by the Multivariable Adaptive digital Controller (MVAC). The MVAC is an adaptive method that continuously adjusts the DC-DC converter switching frequency and dead-time at the same time, while tracking the converter minimum input power, to find the maximum global efficiency point under variable conditions. In this research work, all adaptive methods were discussed, theoretically analyzed and its digital control algorithm along with experimental implementations were presented.

The use of real-time control (RTC) as an adaptation technique for improving existing stormwater systems has been gaining attention in recent years for its ability to enhance water quality and quantity treatment. A case study RTC retrofit of seven existing detention basins was simulated for a small (162 ha), urbanized watershed in Blacksburg, VA. Two heuristic, reactive control algorithms were tested and compared for their ability to improve hydraulic conditions at each detention basin and the watershed outlet through manipulation of an actuated valve, under various permutations of RTC retrofitting (single facility, multiple facilities, etc.). Change in peak flow during 24-hour design storms was assessed. RTC only reduced peak flows at some of the facilities for storms with a return period of 2 years or less. For larger storms, RTC maintained or increased peak flow rates. During a 15-year simulation with historic precipitation data, total duration of erosive flows was reduced for most facility retrofit simulations; however, the duration of high intensity flows increased, or remained unchanged. This result was also reflected at the watershed outlet. / Master of Science / Stormwater management helps protect natural waterways from the harmful impacts of human development. A growing field of research is investigating the potential for “smart” technologies to improve the efficiency of existing stormwater facilities. This study investigates the application of a “smart” stormwater retrofit, known as real-time control (RTC), to existing stormwater management facilities located in a small case study watershed. The RTC system is composed of hypothetical internet-connected sensors and control valves which control flows at several points within the test watershed. Two control algorithms were tested, and compared to the current conditions (scenario with no RTC), for a large range of storm events. Results of this study found that RTC would lead to improved stream health for most rainfall events, but could potentially worsen conditions for the largest, most rare storm events. In addition, RTC was found to be much more effective at some points in the watershed than other points. Prediction of where RTC will be most effective should be the focus of future research.

Yes / This paper presents an iterative learning scheme for vision guided robot trajectory tracking. At first, a stability criterion for designing iterative learning controller is proposed. It can be used for a system with initial resetting error. By using the criterion, one can convert the design problem into finding a positive definite discrete matrix kernel and a more general form of learning control can be obtained. Then, a three-dimensional (3-D) trajectory tracking system with a single static camera to realize robot movement imitation is presented based on this criterion.

Switched reluctance motor has features like robust structure, low cost, and wide speed extension range over conventional induction and synchronous motors. These features make it a promising choice for many applications from electric vehicle to aerospace industry. However, due to its silent structure, the characteristics of switched reluctance motor are highly nonlinear. The nonlinearity makes it difficult to control and results in degraded performance such as high torque ripple and acoustic noise compared with conventional induction machine or synchronous machine. New power converters and control methods have to be developed to improve its performance. In order to reduce the current ripple and torque ripple, a novel three-level converter for switched reluctance motor is proposed. The operation modes and modulation method are presented in detail. Simulation and experimental results show that compared to conventional two-level converter, the proposed three-level converter is able to reduce current ripple, torque ripple and acoustic noise significantly without increasing cost. A fast and accurate current controller is essential for the torque control of switched reluctance motor. An adaptive current controller for the three-level converter is developed to avoid the performance degradation caused by manufacture inconsistency. This controller has the ability to adjust its parameters according to the specific motor it drives. Fast dynamic and high accuracy could be achieved through parameter adaption. In order to reduce the cost, and compete with the well-developed sensorless brushless DC and induction motor drive system, a new position sensorless control method for switched reluctance motor is proposed. This method is effective under both low speed operation and high speed operation. It can start with heavy load. It does not have to align the machine before start up as what is needed for many sensorless brushless DC drive systems. The proposed converter and control methods are all verified by simulation and experimental results. / Thesis / Doctor of Philosophy (PhD)

No description available.

No description available.

No description available.