Thesis (PhD)-Open University. BLDSC no.DX92970.

Thesis (M.S.)--Montana State University--Bozeman, 2005. / Typescript. Chairperson, Graduate Committee: Hashem Nehrir. Includes bibliographical references.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1973. / Typescript. Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1959. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 93-95).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1957. / Typescript. Abstracted in Dissertation abstracts, v. 17 (1957) no. 10, p. 2235. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 147-152).

Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2006. / Dr. Jeffrey Cohen, Committee Member ; Dr. Jerry Seitzman, Committee Member ; Dr. Jeff Jagoda, Committee Member ; Dr. Ben Zinn, Committee Member ; Dr. Tim Lieuwen, Committee Chair.

This thesis deals with the design and application of modern control techniques to a Rolls Royce aircraft gas turbine engine and networked systems. It is motivated by the need to fully exploit recent advances in control engineering and investigate the suitability of various control methods to gas turbine engines and networked systems. The main contributions of the first part of the thesis relate to the gas turbine engine control. Due to the nonlinearities of the gas turbine engines, the rate limiter and saturation constraints on the fuel feed, the aim is to illustrate the potential of a global nonlinear controller to cover the engine operating range. Several nonlinear control methods, gain-scheduling PID controller, approximate model predictive control (AMPC) and nonlinear model predictive control (NMPC), are presented along with the corresponding control algorithms. Since the parameters in a gain-scheduling PID controller change with the operating range, the need is apparent for a global nonlinear controller to cover its operating range. AMPC and NMPC are then demonstrated to be capable of providing a global nonlinear controller for the engine and can be used in the place of the gain scheduling PID controller. It is shown that AMPC is more preferable than NMPC if computational time is at a premium. The main theme of the second part of the thesis is the design and application of the networked predictive control (NPC) to compensate for the network delay and data packet dropout in both forward and backward channels for networked systems. NPC using both modified model predictive control and generic polynomial method is presented along with the corresponding control algorithms. For both approaches, the system stability for a fixed network delay is presented and an analytical stability criterion is obtained. This provides some guidelines on how to choose the NPC parameters in the case of random network delay. The performance of NPC can be further improved by using a robust NPC (RNPC). To validate the performance using the proposed control methods, a servo motor system is then used for both Intranet and Internet based simulations and practical experiments. A networked control test rig along with the network delay measurement method is used for real-time implementation. It is shown that both NPC and RNPC can efficiently compensate for the network delay and data packet dropout in both channels. This thesis provides basis for the real-time implementation of advanced control methods in gas turbine engines. While this work was applied to a gas turbine engine, these techniques can be applied to a range of nonlinear control systems. The work on the networked predictive control presented in this thesis can provide basis for further research relating to this area.

Improvements in the efficiency of power generation via turbomachinery are essential in order to reduce greenhouse gas emissions throughout the world. Advancements in measurement techniques are therefore crucial to understanding the main areas of energy loss in turbines and compressors. This thesis presents a novel system which allows that loss to be characterised using fast response, 3-D measurements of the pressure field within industrial scale rigs. Turbulent energy dissipation rates give an insight into where useable energy is lost from. To gain an insight into such rates, measurement techniques must be able to take data in all three dimensions simultaneously at high sampling rates, usually over 50 kHz. Traditional methods of flow characterisation such as optical techniques and pneumatic pressure probes are unable to capture the rapid fluctuations in pressure and velocity which lead to energy loss from the turbomachine. A new system was therefore designed and implemented into a 6-stage compressor rig to take fast response measurements at sampling frequencies up to 100 kHz behind the last stage stator. A fast-response 5-sensor pressure head, acquired from Kulite Semiconductor Products Inc, has been embedded into a bespoke stem to allow turbulence measurements in a range of turbomachinery applications. The five-sensor (5S) probe was calibrated for pressure sensitivity as well as aerodynamically to give total and static pressure along with velocity magnitude and direction. Individual sensors were calibrated and characterised at temperatures within a range of 200C and 500C, which corresponds to the conditions found within the final application. The probe was also used in a vortex shedding experiment where alternative eddies were detected from the 5S probe measurements in both the time and frequency domain. The aerodynamic calibration of the 5S probe consists of exposing the probe sensors to a range of flow angles in order to map their response between ±200 in both the yaw and pitch directions. This results in four non-dimensional coefficients, two to represent pressure and two to signify the flow angles. A linear interpolation method was written and implemented to deduce pressure and flow angles from experimental query points and the calibration data. The linear interpolation was used as an alternative to the standard surface fit method, where the calibration data is expressed as system of polynomial equations. It was found that the linear method was applicable to the interpolation of flow angles and gave a reduction in computation time of the order of 104. The total and static pressure values do however require the more tried and tested polynomial interpolation method due to the need for higher order interaction terms in the surface fit equation describing the terms. The fully calibrated 5S probe was then implemented into a 6-stage industrial scale rig where it acquired fast response pressure data from the flow field at the exit of the last stage vane. The data was processed to give time resolved, 3-D measurements of total and static pressure, flow angle and velocity. Due to the simultaneous capture of data from all 5 sensors, the resulting velocity vectors can be decomposed into their mean and periodic components to obtain values of energy loss from the turbomachine. The acquisition of such data from an industrial rig marks a novel advancement in the area of turbomachinery flow characterisation and the use of the 5S probe in a range of applications will begin to fulfil the need for a database of fast response data from chaotic and turbulent flow fields.

To provide power on a national scale, a large number of windmills will have to be deployed in wind farms or arrays because the output of individual machines is relatively small. Within an array, some windmills will be faced with the wakes generated by others. This interaction leads to a loss of power relative to upwind turbines and changes in the wind loading across the turbine blades.

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