<p>Power generation using wind turbines is a highly researched control field.</p><p>Many control designs have been proposed based on continuous-time models</p><p>like PI-control, or state observers with state feedback but without special</p><p>regard to robustness to model uncertainties. The aim of this thesis was to</p><p>design a robust digital controller for a wind turbine.</p><p>The design was based on a discrete-time model in the polynomial framework</p><p>that was derived from a continuous-time state-space model based on</p><p>data from a real plant. A digital controller was then designed by interactive</p><p>pole placement to satisfy bounds on sensitivity functions.</p><p>As a result the controller eliminates steady state errors after a step</p><p>response, gives sufficient damping by using dynamical feedback, tolerates</p><p>changes in the dynamics to account for non linear effects, and avoids feedback</p><p>of high frequency un modeled dynamics.</p>

Autoland controllers are prevalent for both large and small/micro unmanned aerial vehicles, but very few are available for medium sized unmanned aerial vehicles. These vehicles tend to have limited sensors and instrumentation, yet must possess good performance in the presence of modeling uncertainties, and exogenous inputs such as turbulence. Quantitative Feedback Theory is an attractive control methodology for this application, since it provides good performance and robustness for systems with structured model uncertainties. It has been successfully applied to many aircraft problems, but not to automatic landing, and only inner-loop synthesis has been presented in the literature. This paper describes the synthesis and development of an automatic landing controller for medium size unmanned aerial vehicles, using discrete Quantitative Feedback Theory. Controllers for the localizer, glideslope tracker, and automatic flare are developed, with a focus on the outer-loops synthesis. Linear, non real-time six degree-of-freedom Monte Carlo simulation is used to compare the Quantitative Feedback Theory controller to a baseline Proportional-Integral controller in several still air and turbulent landing scenarios. The Quantitative Feedback Theory controller provides performance similar to the Proportional-Integral controller in still and in turbulent air. Both controllers show similar robustness to turbulence, but the Quantitative Feedback Theory controller provides significantly better robustness to model uncertainties in turbulent air as well as to sensor characteristics in turbulence. Based on the results of the paper, the QFT controller is a promising candidate for an autoland controller.

Thesis (M.S.)--California State University, Chico. / Includes abstract. "Located in the Chico Digital Repository." Includes bibliographical references (p. 93-94).

Thesis (Ed. D.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains ix, 82 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 75-79).

Thesis (Ph. D.)--University of Hong Kong, 1988.

No description available.

Power generation using wind turbines is a highly researched control field. Many control designs have been proposed based on continuous-time models like PI-control, or state observers with state feedback but without special regard to robustness to model uncertainties. The aim of this thesis was to design a robust digital controller for a wind turbine. The design was based on a discrete-time model in the polynomial framework that was derived from a continuous-time state-space model based on data from a real plant. A digital controller was then designed by interactive pole placement to satisfy bounds on sensitivity functions. As a result the controller eliminates steady state errors after a step response, gives sufficient damping by using dynamical feedback, tolerates changes in the dynamics to account for non linear effects, and avoids feedback of high frequency un modeled dynamics.

Increasing power consumption and heat dissipation are becoming urgent challenges for processors today and in the future. Digital power control architectures in which processors closely interact with voltage regulators are becoming necessary to enhance system energy efficiency. Digital techniques offer advantages such as flexibility, fewer external components and reduced overall cost as compared to conventional analog techniques. The primary objective of this thesis is to develop new digital control architecture for processor voltage regulators with low complexity and high dynamic performance. A digital control technique to naturally implement the desired output impedance is proposed. In this technique, Adaptive Voltage Positioning (AVP) is implemented by generating a dynamic voltage reference and a dynamic current reference to achieve the desired output impedance. A dual-voltage-loop control with dynamic reference step adjustment, non-linear control and a dedicated transient detection circuit is proposed to improve the dynamic performance. The dynamic reference step adjustment method lowers the high speed requirement of reference update clock; the non-linear control minimizes the transient-assertion-to-action delay and maximizes the inductor current slew rate; and the transient detection circuit recognizes the load transient state in a manner adaptive to the amount and slew rate of load transient. Theoretical, simulation and experimental results prove the effective operation and excellent performance of the controller. Finally, the dynamic performance of the voltage regulator with the proposed digital controller under large-step load oscillations is proven by simulation and experimental results. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2008-07-31 13:14:52.149

Primarily because of its low cost and ease of implementation, analogue control has been the dominant control strategy in modern switch-mode power supply designs. The 'on/off' nature of power switches is essentially digital, which makes it tempting for power elec- tronics engineers to combine the emerging capability of digital technologies with existing switch-mode power supply designs. Whereas an analogue controller is usually cheaper to implement, it lacks the flexibility and capacity to implement the complex control func- tions which a digital controller can offer. The research presented in this thesis addresses the practical implementation of a digi- tal controller for a Series-Loaded Resonant Converter (SLR). The resonant frequency of the SLR converter is around 60 kHz, and the switching frequency varies up to around 80 kHz to regulate the 12V dc output voltage across a 100W, variable resistive load, from a variable 46.6V 60.2V input voltage. This provides a fair challenge for digital waveform generators as the digital processor needs to have a high clock rate to produce high speed, high resolution and linearly varying frequency square waves, to regulate the output volt- age with adequate resolution. Digital compensation algorithms also need to be efficient to minimise the phase lag caused by the instruction overhead. In order to completely understand the control needs of the SLR converter, an analogue controller was constructed using a UC3863N. The feedback compensation consists of an error amplifier in an integrator configuration. Digital control is accomplished with a TMS320F2812 Digital Signal Processor (DSP). Its high throughput of 150 MIPS provides sufficient resolution to digitally generate linearly varying frequency switching signals util- ising Direct Digital Synthesis (DDS). Time domain analysis of the switching signals, shows that the DDS generated square iv ABSTRACT waves display evidence of jitter to minute variations in pulse-widths caused by the digi- tisation process, while in the frequency domain, this jitter displays itself as additional sidebands that deteriorate the fundamental frequency of the switching signal. Overall, DDS generated square waves are shown experimentally to be adequate as control signals for the MOSFET power switches. Experiments with step load changes show the digi- tal controller is able to regulate the output voltage properly, with the drawback of the settling time being a little longer than the analogue counterpart, possibly caused by the unpredictable damping effects of switching signal jitter. Variations in input voltage shows that the digital controller excels at operating under noisier conditions, while the analogue controlled output has slightly greater noise as input voltage is increased. As the digital technology continues to improve its speed, size and capacity, as well as becoming more affordable, it will not be long before it becomes the leading form of control circuitry in power supplies.

This thesis is concerned with the True Digital Control (TDC) design philosophy and its practical embodiment in the non-minimal state space (NMSS) approach to control design, for systems described by discrete time transfer function models in the backward shift operator. This yields Proportional-Integral-Plus (PIP) controllers that are particularly easy to implement in practice, since the state variables are defined only in terms of the sampled input and output signals. The basic PIP algorithm is extended and enhanced in various ways to form a more sophisticated Generalised PIP controller. This includes an investigation into the importance of structure in PIP control design, the development of a command input anticipation technique and the introduction of two stochastic formulations of the problem, namely Kalman Filtering and risk sensitive optimal control. Finally, the thesis discusses the relationship between PIP and predictive control, in particular Generalised Predictive Control (GPC) and the Smith Predictor. The power of the approach is illustrated by the design of PIP controllers for a number of difficult applications also described in the thesis, including the control of a large horticultural greenhouse at Silsoe Research Institute; the control of carbon dioxide in crop growth experiments; the control of a Statistical Traffic Model simulation of interurban traffic networks; and, finally, the control of the multivariable Shell heavy oil fractionator simulation.