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Data centers operations are notoriously energy-hungry, with the computing and cooling infrastructures drawing comparable amount of electrical power to operate. A direction to improve their efciency is to optimizethe cooling, in the sense of implementing cooling infrastructures controlschemes that avoid performing over-cooling of the servers.Towards this direction, this work investigates minimum cost linearquadratic control strategies for the problem of managing air cooled datacenters. We derive a physical and a black box model for a general datacenter, identify this model from real data, and then derive, present andtest in the eld a model based Linear-Quadratic Regulator (LQR) strategy that sets the optimal coolant temperature for each individual coolingunit. To validate the approach we compare the eld tests from the LQR strategy against classical Proportional-Integral-Derivative (PID) controlstrategies, and show through our experiments that it is possible to reducethe energy consumption with respect to the existing practices by severalpoints percent without harming the servers within the data center fromthermal perspectives.

The main part of this licentiate thesis concerns parallelization of recursive estimation methods, both linear and nonlinear. Recursive estimation deals with the problem of extracting information about parameters or states of a dynamical system, given noisy measurements of the system output and plays a central role in many applications of signal processing, system identification, and automatic control. Solving the recursive Bayesian estimation problem is known to be computationally expensive, which often makes the methods infeasible in real-time applications and for problems of large dimension. As the computational power of the hardware is today increased by adding more processors on a single chip rather than increasing the clock frequency and shrinking the logic circuits, parallelization is the most powerful way of improving the execution time of an algorithm. It has been found in this thesis that several of the optimal filtering methods are suitable for parallel implementation, in certain ranges of problem sizes. It has been concluded from the experiments that substantial improvements can be achieved by performing "tailor"-made parallelization, compared to straightforward implementations based on multi-threaded libraries. For many of the suggested parallelizations, a linear speedup in the number of cores has been achieved that have provided up to 8 times speedup on a double quad-core computer. As the evolution of the parallel computer architectures is unfolding rapidly, many more processors on the same chip will become available. The developed methods do not, of course, scale infinitely, but definitely can exploit and harness some of the computational power of the next generation of parallel platforms, allowing for optimal state estimation in real-time applications.

Reliable sensor values are important for resource-efficient control and operations of wastewater treatment processes. Automatic fault detection methods are necessary to monitor the increasing amount of data produced in any modern water resource recovery facility (WRRF). Most on-line measurements exhibit large variations under normal conditions, due to considerable variations in the influent flow. The work reported in this licentiate thesis deals with fault detection in WRRFs. In the first paper, we studied how Gaussian process regression (GPR), a probabilistic machine learning method, could be applied for fault detection in WRRFs. The results showed that the standard parameter estimation method for GPR suffered from local optima which could be solved by instead estimating the distribution of the parameters with a sequential Monte Carlo algorithm (GPR-SMC). The GPR-SMC allowed for automatic estimation of missing data in a simulated influent flow signal with high noise, which is a representative signal for on-line sensors in WRRFs. In addition, the GPR-SMC provided uncertainty predictions for the estimated data and accurate sensor noise estimates. Care should be taken in selecting a suitable kernel for GPR, since the results were in contrast to the general assumption that prior knowledge can easily be encoded by means of selecting a proper kernel. Here, the autocorrelation graph was found useful as diagnostic tool for selecting a proper kernel. In the second paper, we studied how active fault detection (AFD) could be used to reveal information about the sensor status. The AFD was implemented by evaluating the change in a dissolved oxygen (DO)-signal caused by the sensor's automatic cleaning system. Fault signatures were obtained for fouling and several other sensor faults such as a worn out or mechanically damaged membrane. This demonstrates the potential of AFD, not only for fault detection, but also for fault diagnosis. Interestingly, the progression of the sensor bias due to organic biofilm fouling differed depending on the measurement technique used within the DO-sensor. This is new knowledge that is valuable for process control and should be further studied. The AFD was implemented on a full scale system to demonstrate its applicability, which is rarely done in research papers in the field of WRRFs.

Abstract Teaching in the university has been under pressure to change in recent years. On the one hand, there is financial pressure to decrease resources on the other, there is a need to keep quality and quantity of education offered high and to give due consideration to changes in technology and learning methods. One response to these pressures has been to study if it is possible to build a learning environment for Control Engineering that is available to students virtually. It could help to distribute materials and facilitate overall communication, from course information through student feedback. It could also make studying more efficient by enabling better follow-up of learning and use of interactive functions. The development of a Web-based learning environment for Control Engineering started from a simple model of learning theories and course content. This model was applied to that context, and an open learning environment was developed and implemented. The implementation is referred to as Control Web. Functions were added to Control Web and tuned according to student feedback. The probe method was utilised in the validation. Two courses were subjected to under full validation in order to carry out validation for the whole system. Student feedback, grades, and credits during the years 1993 to 2000 were analysed. According to the results, the system implemented has performed well. However, the explicit influence of using the Web-based learning environment can be seen in only few cases; there are too many variables in the overall learning situation. The results and experiences yield an enhanced model for developing a learning environment and a tool that indicates a need to change course parameters.

This project describes the design and assembly of the power electronic and control system for variable speed control of a micro scale hydro power station in Sweden. The turbine is a new type of integrated turbine-generator unit, called Turbo, designed by prof. Urban Lundin at Uppsala University. Power electronic components was dimensioned, purchased and assembled. The projects purpose is to create an installation for testing and evaluation of Turbo and the main goal was to determine Turbos optimal rotational speed. A commercial 20 kW solar power inverter from Fronius was used and it was controlled using LabVIEW and communicating through the serial protocol Modbus. To control the rotational speed of the generator a PI-regulator with negative feedback was used and controlled from LabVIEW. Test results shows a functioning system where the inverter is to slow to work in an optimal way. This is likely due to the fact that solar power inverters doesn't have to regulate as fast as inverters designed for hydro- and windpower. When testing the integrated turbine generator on site it didn't rotate and final tests could therefore not be completed. This might be because of a bearing that is not properly designed and further research on the area must therefore be completed before determining the optimal rotational speed.

Process optimization is used to improve the utility and the economic performance of industrial processes, and is as such central in most automation strategies. In this thesis, two feedback-based methods for online process optimization are considered: Extremum seeking control (ESC), a classic model-free method used for steady-state optimization which dates back to the early 1900's, and economic model predictive control (EMPC), a more recent method which utilizes a model to dynamically optimize the closed-loop process economics in real time. Part I of the thesis concerns ESC. Due to a well known result by Krsti\'c and Wang, it is known that the classic ESC-loop will possess a stable stationary solution in a neighborhood of the optimum when applied to dynamic plants. However, existence and stability of an optimal solution alone are not sufficient to guarantee that the ESC-loop will converge to the optimum; uniqueness also has to be considered. In this thesis, it is shown that the near-optimal solution is not necessarily unique, not even in cases where the objective, i.e., the steady-state input-output map, is convex. The stationary solutions to the loop are shown to be characterized by a condition on the local plant phase-lag, and for a biochemical reactor it is found that this condition can be satisfied not only locally at the optimum but also at arbitrary points away from the optimum. Bifurcation theory is used to show that the observed solution multiplicity may be explained by existence of fold bifurcation points, and conditions for existence of such points are given. The phase-lag condition for stationarity combined with the result by Krsti\'c and Wang suggest that the process phase-lag is connected to steady-state optimality. In this thesis, it is shown that the steady-state optimum corresponds to a bifurcation of the plant zero dynamics which is reflected in large local phase-lag variations. This explains why the classical ESC method will have a near-optimal stationary solution when applied to dynamic plants, and it also shows that a steady-state optimum may be located using only phase information. Finally, we introduce greedy ESC which is applicable to plants where the dynamics may be separated into different time-scales. By optimizing only the fast plant-dynamics, significant performance improvements may be achieved. Part II of this thesis concerns EMPC. The method is first evaluated for optimization of a paper-making process by means of simulations. These reveal several important properties of EMPC, e.g., that EMPC in the presence of excessive degrees of freedom automatically selects the inputs which are currently most efficient, and that EMPC effectively plans ahead which leads to significantly improved performance during grade changes. However, it is also observed that EMPC often operates with constraints active since economic objectives frequently are monotone, and this may lead to issues with robustness. To avoid active constraints, constraint margins are introduced to force the closed-loop to operate in the interior of the feasible set. The margins affect the economic performance significantly and the optimal choice is dependent on the uncertainty present in the problem. To avoid modeling of the uncertainty, it is suggested that the margins are adapted based on feedback from the realized closed-loop economic performance. / <p>QC 20180829</p>

Vibration isolation is a procedure through which the transmission of oscillating disturbances or forces is reduced. The ideal isolator is one that will support the equipment being isolated without transmitting any dynamic forces. An isolator with infinite static stiffness and zero dynamic stiffness will achieve this goal. Although this ideal isolation cannot be obtained in practice, it can be approximated through a wide range of devices. This approximation occurs over a limited frequency band and methods of increasing this band were investigated. The goal of this thesis was to further our understanding of mechanical systems that can approximate the ideal isolator behaviour. To compare the various devices the blocked transfer dynamic stiffness was defined. This value was found to represent the isolator properties without the additional complication of the equipment being isolated as happens in traditional transmissibility methods. Three classes of devices were distinguished namely isolators, vibration-absorbing isolators (VAl) and amplified vibration-absorbing isolators (AVAI). The last two types exploit nodalisation to reduce the dynamic stiffness over a limited frequency range. The focus of this work is the broadening of the effective low stiffness bandwidth of amplified vibration-absorbing isolators by adapting system characteristics. If the excitation is tonal time-varying these devices can be used successfully. Two novel adaptive amplified vibration-absorbing isolators were introduced and studied in the time and frequency domains. The type I AVAI uses flexible reservoir walls to vary the isolation frequency. The type II device incorporates a heavy metal slug. Both devices use variable pressure air springs to change their stiffness. The use of air springs are convenient, offers low damping and can be used in an application such as a pneumatic rock drill handle to eliminate the need for a control system. Conceptual design methodologies for both damped and un-damped fixed and adaptive isolation frequency AVAls are presented. To determine the effects of tuning the equations were transformed in terms of constant frequency ratios and the variable stiffness ratio. The devices can be controlled using an optimisation approach, but care should be taken since the method could be unsuccessful in some cases. The design was then applied to a pneumatic rock drill. This application was particularly demanding because the stiffness had to be large enough for the operator to remain in control of the drill, yet low enough to offer isolation. Extensive measurements of drill vibration at a test facility found that the maximum acceleration values were 18.72 m/s2. The maximum allowed under the proposed European Union legislation is 10 m/s2 for short durations. The excitation consisted of a large tonal component and wide-band noise. The tonal component contributed ~50% of the total weighted equivalent acceleration experienced by the operator and a vibration absorbing isolator should therefore be an ideal solution. The measurements also showed that the excitation frequency is a function of the supply air pressure. By using the supply air pressure to feed the air spring the device could be made self-¬tuning. Numerical simulation showed that there is only a slight difference between using the supply pressure and forcing coincidence of the excitation and isolation frequencies. It was also found that the vibration levels could be reduced to below 10 m/s2<./sup> in some cases. / Thesis (PhD (Mechanical Engineering))--University of Pretoria, 2006. / Mechanical and Aeronautical Engineering / unrestricted

With the recent push towards autonomous cars, a traditional steering wheel with its mechanical connection between the road and driver may soon be unnecessary. To facilitate interior design and lower production costs whilst still maintaining a manual alternative for maneuvering, an alternative steering input device relying on Steer-by-Wire technology is investigated. In order to finish the investigation and development of the steering device within the time-span of a master thesis, the limitation to only investigate the design of a hand wheel was established. The finished alternative steering device utilises an optical encoder for position measurement and a brushless direct current (DC) motor with a planetary gearbox for force feedback. Open-loop speed control proved to be insufficient with the available hardware. Instead, an approach of two PD-controllers regulating the angular error between the steering rack and the steering device was implemented successfully. Initially, mathematical models of the system components were derived and implemented in Mathworks Simulink. The transition from models to test rig implementation proved to be difficult due to unknown parameters in the hardware components such as embedded controllers in the steering gear and the internal works of the sensor emulator used to control the steering gear. By modifying parameters in accordance with system identification measurements performed on the test rig, the models could be validated. At the end of the project, a Volvo S60 was made available and the steering device was tested with real world driving. It was discovered that controllers tuned only for good reference following in the test rig did not translate to good driveability as the controller allowed for overly aggressive maneuvers. Following some in vehicle tuning, the proposed solution performed well during testing with surprisingly high drive-ability. For future iterations of similar hand wheel design projects, a user study was performed with regards to user experience, hand wheel size and perceived driveability.

Glava Energy Center har gett mig i uppdrag att skapa ett system som kan hantera mätdatainsamling för solceller. Projektet går ut på att mäta ström och spänning från solceller och sedan skicka denna mätdata till en metrum instrumentlåda som sedan laddar upp datan till deras databas. Med hjälp av ett mikrokontrollerkort och en IC skapas detta system för att hämta data. Datan kollas sedan via python kod för att se så att den stämmer väl med vad som förväntas. Systemet som utvecklats hittar solcellens MPP inom 20 sekunder. Dock tack vare tidsbrist kan inte systemet skapa den analoga signalen på 4-20mA som krävs för att skicka datan till metrum instrumentlådan. Den teoretiska kretsen är färdig men har inte hunnit implementeras. / <p></p><p></p>