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This thesis aims to understand how to design high-performance compression algorithms suitable for hardware implementation and to provide hardware support for an efficient compression algorithm. Lossless data compression techniques have been developed to exploit the available bandwidth of applications in data communications and computer systems by reducing the amount of data they transmit or store. As the amount of data to handle is ever increasing, traditional methods for compressing data become· insufficient. To overcome this problem, more powerful methods have been developed. Among those are the so-called statistical data compression methods that compress data based on their statistics. However, their high complexity and space requirements have prevented their hardware implementation and the full exploitation of their potential benefits. This thesis looks into the feasibility of the hardware implementation of one of these statistical data compression methods by exploring the potential for reorganising and restructuring the method for hardware implementation and investigating ways of achieving efficient and effective designs to achieve an efficient and cost-effective algorithm.

In general digital control algorithms are multi-input multi-output (MIMO) recursive digital filters, but there are particular numerical requirements in control system processing for which standard processor devices are not well suited, in particular arising in systems with high sample rates. There is therefore a clear need to understand the numerical requirements properly, to identity optimised forms for implementing control laws, and to translate these into efficient processor architectures. By taking a considered view of the numerical and calculation requirements of control algorithms, it is possible to consider special purpose processors that provide well-targeted support of control laws. This thesis describes a compact, high-speed, special-purpose processor which offers a low-cost solution to implementing linear time invariant controllers.

Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Mavris, Dimitri; Committee Member: German, Brian; Committee Member: Healy, Tim; Committee Member: Rosson, Randy; Committee Member: Tai, Jimmy. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (Ph. D.)--Rutgers University, 2008. / "Graduate Program in Chemical and Biochemical Engineering." Includes bibliographical references (p. 268-270).

archives@tulane.edu / This dissertation is a detailed scientific study concerning a proton exchange membrane fuel cell, which is coupled to a DC-to-DC converter as the power processor, serving as a power source. The novel aspect of the dissertation is the use of a new controller or nonlinear observer to predict parameter estimation of the fuel cell and the DC-to-DC converter as the load potential changes for the automated control system. Nonlinear control algorithms, which include nonlinear observers, were developed for such systems. / 1 / Sean

ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / A digital antenna control system has been designed and installed on a pedestal that was formerly used to drive a VHF array and that has now been replaced with an 11 meter S-Band parabolic reflector. In this Paper, the former analog tracking system will be described, showing all the drawbacks that made it unusable for S-Band. Subsequently, the development and implementation of the digital S-Band tracking system, using Labview, C++ & digital control theory will be discussed. Finally, there will be a comparison between the digital and analog system, too.

Model predictive control (MPC) has gained great acceptance in the industry since it was developed and first applied about 25 years ago [1]. It has established its place mainly in the advanced control community. Traditionally, MPC configurations are developed and commissioned by control experts. MPC implementations have usually been only worthwhile to apply on processes that promise large profit increase in return for the large cost of implementation. Thus the scale of MPC applications in terms of number of inputs and outputs has usually been large. This is the main reason why MPC has not made its way into low-level loop control. In recent years, academia and control system vendors have made efforts to broaden the range of MPC applications. Single loop MPC and multiple PID strategy replacements for processes that are difficult to control with PID controllers have become available and easier to implement. Such processes include deadtime-dominant processes, override strategies, decoupling networks, and more. MPC controllers generally have more "knobs" that can be adjusted to gain optimum performance than PID. To solve this problem, general PID replacement MPC controllers have been suggested. Such controllers include forward modeling controller (FMC)[2], constraint LQ control[3] and adaptive controllers like ADCO[4]. These controllers are meant to combine the benefits of predictive control performance and the convenience of only few (more or less intuitive) tuning parameters. However, up until today, MPC controllers generally have only succeeded in industrial environments where PID control was performing poorly or was too difficult to implement or maintain. Many papers and field reports [5] from control experts show that PID control still performs better for a significant number of processes. This is on top of the fact that PID controllers are cheaper and faster to deploy than MPC controllers. Consequently, MPC controllers have actually replaced only a small fraction of PID controllers. This research shows that deficiencies in the feedback control capabilities of MPC controllers are one reason for the performance gap between PID and MPC. By adopting knowledge from PID and other proven feedback control algorithms, such as statistical process control (SPC) and Fuzzy logic, this research aims to find algorithms that demonstrate better feedback control performance than methods commonly used today in model predictive controllers. Initially, the research focused on single input single output (SISO) processes. It is important to ensure that the new feedback control strategy is implemented in a way that does not degrade the control functionality that makes MPC superior to PID in multiple input multiple output (MIMO) processes. / text

Thesis (Ph.D.)--University of Melbourne, Dept. of Computer Science and Software Engineering, 2010. / Typescript. Includes bibliographical references (p. 153-167)

Recently, decentralized household photovoltaic (PV) systems have become more affordable and there is a tendency to decrease subsidies for the PV excess electricity fed into the grid. Therefore, there is growing interest in methods to increase the self-consumption (SC), which is the part of the electricity produced by PV and directly consumed on buildings. It has been found that battery storage is an effective way to achieve this. When there is a heat pump system installed, thermal energy storage using the thermal mass of the building or hot water tanks, can also be used to increase the household self-sufficiency and minimize the final energy use. The main aim of this thesis is to develop operational control strategies for the heating system of a single-family house with an exhaust air heat pump, a photovoltaic system and energy storage. In order to accomplish this a detailed system model was developed in TRNSYS 17, which includes a six-zone building model and the heat pump control. Moreover, these control strategies include short-term weather and price forecast services.  Another objective is to evaluate the impact on the benefit of these control strategies in terms of energy use and economic performance for a wide range of boundary conditions (country/climate, electricity prices, occupancy and appliance loads).  Results show that the control using a forecast of dynamic electricity price in most locations leads to greater final energy savings than those due to the control using thermal storage for excess PV production. The exception is Sweden, where the result is the opposite. Moreover, the addition of battery storage leads to greater decreases in final energy than the use of the thermal storage (TH mode), which is limited to the thermal mass of the building and small hot water tank of the compact heat pump. As far as the impact of the advanced control (combined use of TH and PRICE) on cost savings is concerned, savings (up to 175 €) are possible in Spain and in Germany. The design of the TH and PRICE mode show low computational complexity that can be easily implemented in existing heat pump controllers. Additionally, the PRICE mode should have no capital and running cost for the end user while the TH mode might require an external electricity meter. Another yet implication with the TH mode is the need to activate the room thermostatic valve.