In this thesis, we present selected methods of regression and classification analysis in terms of robust optimization which aim to compensate for data imprecisions and measurement errors. In the first part, ordinary least squares method and its generalizations derived within the context of robust optimization - ridge regression and Lasso method are introduced. The connection between robust least squares and stated generalizations is also shown. Theoretical results are accompanied with simulation study investigating from a different perspective the robustness of stated methods. In the second part, we define a modern classification method - Support Vector Machines (SVM). Using the obtained knowledge, we formulate a robust SVM method, which can be applied in robust classification. The final part is devoted to the biometric identification of a style of typing and an individual based on keystroke dynamics using the formulated theory. Powered by TCPDF (www.tcpdf.org)

Geodätische Messabweichungen werden oft gut durch Wahrscheinlichkeitsverteilungen beschrieben, die steilgipfliger als die Gaußsche Normalverteilung sind. Das gilt besonders, wenn grobe Messabweichungen nicht völlig ausgeschlossen werden können. Neben einigen in der Geodäsie bisher verwendeten Verteilungen (verallgemeinerte Normalverteilung, Hubers Verteilung) diskutieren wir hier die skalenkontaminierte Normalverteilung, die für die praktische Rechnung einige Vorteile bietet. / Geodetic measurement errors are frequently well described by probability distributions, which are more peak-shaped than the Gaussian normal distribution. This is especially true when gross errors cannot be excluded. Besides some distributions used so far in geodesy (generalized normal distribution, Huber’s distribution) we discuss the scale contaminated normal distribution, which offers some advantages in practical calculations.

Over the last few decades, many factors, including increased electrification, have led to a critical need for fast and efficient transient cooling. Thermal management systems (TMSs) are typically designed using steady-state assumptions and to accommodate the most extreme operating conditions that could be encountered, such as maximum expected heat loads. Unfortunately, by designing systems in this manner, closed-loop transient performance is neglected and often constrained. If not constrained, conventional design approaches result in oversized systems that are less efficient under nominal operation. Therefore, it is imperative that \emph{transient} component modeling and subsystem interactions be considered at the design stage to avoid costly future redesigns. Simply put, as technological advances create the need for rapid transient cooling, a new design paradigm is needed to realize next generation systems to meet these demands. <br><br>In this thesis, I develop a new design approach for TMSs called hierarchical control co-design (HCCD). More specifically, I develop a HCCD algorithm aimed at optimizing high-fidelity design and control for a TMS across a system hierarchy. This is accomplished in part by integrating system level (SL) CCD with detailed component level (CL) design optimization. The lower-fidelity SL CCD algorithm incorporates feedback control into the design of a TMS to ensure controllability and robust transient response to exogenous disturbances, and the higher-fidelity CL design optimization algorithms provide a way of designing detailed components to achieve the desired performance needed at the SL. Key specifications are passed back and forth between levels of the hierarchy at each iteration to converge on an optimal design that is responsive to desired objectives at each level. The resulting HCCD algorithm permits the design and control of a TMS that is not only optimized for steady-state efficiency, but that can be designed for robustness to transient disturbances while achieving said disturbance rejection with minimal compromise to system efficiency. Several case studies are used to demonstrate the utility of the algorithm in designing systems with different objectives. Additionally, high-fidelity thermal modeling software is used to validate a solution to the proposed model-based design process. <br>

This thesis proposes a distributed robust control approach for low-thrust nanosatellite formation flying. The presented control approach is the further development of an already existing approach which combines robust control and distributed control using the consensus approach. The adjustments presented in this thesis are intended to enable the usage of the control approach in nanosatellite missions such as the upcoming NetSat mission. Stability criteria, optimization goals and constraints such as the limited maximum thrust are formulated with the help of Linear Matrix Inequalities (LMIs). In addition, the presented control approach includes methods for exploiting the maximum thrust and for collision avoidance. Due to the design as a distributed controller based on the consensus approach, a satellite formation can be maintained even in the case of the failure of the propulsion system and/or Attitude Determination and Control System (ADCS) of a single satellite. To verify the design of the control approach, simulations of the formation scenarios planned for the NetSat mission are performed with a satellite formation simulation framework based on Orekit and MATLAB®.

The autocorrelation function is a basic tool for time series analysis. The clas- sical estimation is very sensitive to outliers and can lead to misleading results. This thesis deals with robust estimations of the autocorrelation function, which is more resistant to the outliers than the classical estimation. There are presen- ted following approaches: leaving out the outliers from the data, replacement the average with the median, data transformation, the estimation of another coeffici- ent, robust estimation of the partial autocorrelation function or linear regression. The thesis describes the applicability of the presented methods, their advantages and disadvantages and necessary assumptions. All the approaches are compared in simulation study and applied to real financial data. 1

The electric power industry and society are facing the challenges and opportunities of transforming the present power grid into a smart grid. To meet these challenges, new types of control systems are connected over IT infrastructures. While this is done to meet highly set economical and environmental goals, it also introduces new sources of uncertainty in the control loops. In this thesis, we consider control design taking some of these uncertainties into account. In Part I of the thesis, some economical and environmental concerns in smart grids are taken into account, and a scheduling framework for static loads (e.g., smart appliances in residential areas) and dynamic loads (e.g., energy storage systems) in the distribution level is investigated. A robust formulation is proposed taking the user behavior uncertainty into account, so that the optimal scheduling cost is less sensitive to unpredictable changes in user preferences. In addition, a novel distributed algorithm for the studied scheduling framework is proposed, which aims at minimizing the aggregated electricity cost of a network of apartments sharing an energy storage system. We point out that the proposed scheduling framework is applicable to various uncertainty sources, storage technologies, and programmable electrical loads. In Part II of the thesis, we study smart grid uncertainty resulting from possible security threats. Smart grids are one of the most complex cyber-physical systems considered, and are vulnerable to various cyber and physical attacks. The attack scenarios consider cyber adversaries that may corrupt a few measurements and reference signals, which may degrade the system’s reliability and even destabilize the voltage magnitudes. In addition, a practical attack-resilient framework for networked control systems is proposed. This framework includes security information analytics to detect attacks and a resiliency policy to improve the performance of the system running under the attack. Stability and optimal performance of the networked control system under attack and by applying the proposed framework, is proved here. The framework has been applied to an energy management system and its efficiency is demonstrated on a critical attack scenario. / <p>QC 20160830</p>

Geometrical variation is an unavoidable aspect in all types of manufacturing that may, unless managed, risk failure in fulfilling product requirements which may result in rework, delays and bad publicity. The term geometry assurance includes the tools, methods and processes that can be utilized to manage the effects of geometrical variation and to ensure fulfillment of esthetical, functional and assembly requirements. While state of the art research in geometry assurance is extensively applied within the automotive and aerospace industries with great success, its application in low volume manufacturing of complex products remains limited. The shipbuilding industry is an example of such an industry, often manufacturing large and complex products in low quantities. Further, the shipbuilding industry has historically been labor-intensive and relied on craftsmanship throughout the product realization process. However, studies indicate that a technology-intensive development is crucial for companies in order to maintain market competitiveness. This transition places high demands on a well-established geometry assurance process in order to ensure successful assembly and fulfillment of product requirements.  In this thesis, a feasibility study is conducted on how geometry assurance may be applied in low volume manufacturing of complex products. By developing guidelines on how geometry assurance may be applied, the purpose is to improve geometrical quality throughout the product realization process and to reduce lead times, costs and increase assembly precision.  To explore the feasibility of geometry assurance in low volume manufacturing of complex products, a work structure consisting of three phases was established. In the first phase, a current state analysis of the collaboration partner Saab Kockums was conducted parallel to studying state of the art research in geometry assurance. In phase two, the state of practice of companies in the automotive and aerospace industries was studied in order to determine how they apply state of the art research. By interviewing industry specialists and combining gained knowledge from the first two phases, guidelines on how geometry assurance may be applied in low volume manufacturing of complex products was developed. In phase three, based on these guidelines, suggestions on how the geometry assurance process in pipe manufacturing at Saab Kockums can be improved was developed. The results of this study indicate that geometry assurance is applicable in low volume manufacturing of complex products. However, alternative methods may be required. Based on gained knowledge and insights from interviews with industry specialists, guidelines on how geometry assurance in low volume manufacturing of complex products may be applied are proposed. In order to improve the geometry assurance process in pipe manufacturing at Saab Kockums, this study proposes general guidelines for improvement along with a process and prototype measurement tool for the fitting-pipe methodology. The specially designed prototype measurement tool presents an alternative measurement method that can be used in cramped spaces where it is difficult to access with a 3D-measurement arm, the proposed primary measurement technique. In conclusion, this study indicates that geometry assurance is applicable in low volume manufacturing of complex products and suggests three methods for how it may be achieved. However, each of these methods needs to be further investigated in order to determine their applicability in other low volume manufacturing industries. Further, the prototype measurement tool and process for the fitting-pipe methodology indicates potential for improving the geometry assurance process in pipe manufacturing. However, further work is needed to complete the process for fitting-pipes and to finalize the prototype measurement tool for production use.

Syfte: Fallstudien ämnade att undersöka möjliga förbättringsområden som kan förbättravårdsäkerheten för patienter genom att skapa en mer robust försörjning av förbrukningsmaterial(FM). Genom att göra sjukvård vid normalläge robust skapas möjlighet att även vara mer robustunder kris. Metod: En fallstudie baserad på kvalitativa intervjuer med inblandade intressenter vilketgenererade underlag för att identifiera försörjningskedjan av FM till Akademiska sjukhuset(AS) samt för att använda en tematisk analysmetod. Resultat: Den tematiska analysen resulterade i 5 huvudteman och 18 koder därförbättringsområden kunde belysas. De huvudteman som identifierades var förbrukningslagerpå avdelningar, leveranssäkerhet, kvalitet, informationsdelning och robusthet.Förbättringsområdena sammanställdes i en handlingsstrategi som bestod av förbättringsstegsom ämnar att bidra till att uppnå förbättringar inom de 18 identifierade koderna.Handlingsstrategin bestod av fyra steg vilka var automatiserad informationsdelning,standardiserade rutiner, kravställning och krisberedskap. Slutsats: Genom att försörjningskedjan blir mer robust ökar chansen att sjukvård finnstillgänglig för att tillgodose patientens behov. Från den tematiska analysen identifieradessuboptimeringar vilka kan åtgärdas i form av behovssamordning, informationsdelning,skapande av rutiner, kravställning och krisberedskap. Det anses vara områden som börförbättras för att en robust sjukvård ska kunna uppnås i normalläge och vid kris.

One of the major challenges hindering advancement of quantum computing is the sensitive nature of the physical systems used to build a quantum computer. One suggestion for improving reliability is a particular type of logic gates, based on Berry's geometric phase, showing improved robustness to external disturbance of the quantum system over the course of a calculation. Such logic gates have previously been shown for the smallest possible two-level qubits. Using the method of adiabatic shortcut we endevour to discover similarly realistic and robust logic gates for units of quantum information in higher dimensions. The example shown in this paper discusses three-level qutrits, but is expected to apply to theoretically unlimited higher dimensions since new geometric complications are expected to arise primarily when moving from a two-level to a multi-level problem.  We here present a set of primitive single-qutrit gates able to perform universal quantum computations if supplemented by a two-qutrit gate. We also present a set of condensed single-qutrit gates for commonly needed operations. By detailing the underlying mathematical framework, relying on the multi-dimensional generalisation of Berry's phase describing the time evolution of degenerate quantum states, we also suggest an easily scalable geometric interpretation of quantum gates in higher dimensions along with visual representation of logic gates using parameters of the physical system to sequentially unlock and manipulate subspaces of the quantum information unit.

Management of water resources is afflicted with uncertainties. Nowadays it is facing more and new uncertainties since pace and dimension of changes (e.g. climatic, demographic) are accelerating and are likely to increase even more in the future. Hence it is crucial to find pragmatic ways to deal with these uncertainties in water management. This thesis argues for an analytical yet pragmatic approach to enable decision-makers to deal with uncertainties in a more explicit and systematic way and allow for better informed decisions. The approach is based on the concept of framing and mental models, referring to different ways in which people make sense of the world and of uncertainties. It is analysed how uncertainties are framed and dealt with in water management practice and strategies are elaborated how dealing with uncertainties can be improved in water management practice. The research for this thesis has been closely linked to the EU research project NeWater (New Approaches to Adaptive Water Management under Uncertainty, www.newater.uos.de) (2005-2009). It draws on practical experiences of water managers at local and regional level in river basin management in three case studies, i.e. the German Wupper, the Dutch Kromme Rijn, both sub basins of the river Rhine, and the Doñana region located in the Guadalquivir Estuary in Spain. For the assessment of framing of uncertainty two different methods were developed and applied in the three river basins. Both aim at identifying parameters of importance in the process of framing uncertainty in order to understand how uncertainties get framed. The empirical research confirmed that indeed water managers are faced with a range of uncertainties and that so far no systematic approaches are applied for dealing with those in management practice. The results in the case studies suggest that there are no universal findings as to how actors frame uncertainties but rather that framings are dependent on the respective uncertainty situation, on roles (e.g. project leader, public administration, scientist etc.), and most often on personal traits. The case study findings moreover suggest that there are no universally valid parameters of influence in the framing of uncertainties. Neither could a clear superiority of one approach over the other be discerned. Nonetheless, the parameters of framing of uncertainty proved to be a supportive tool for preparing and structuring decision-making in the case studies and developing improvement options for dealing with uncertainty. Beyond the results of the development of approaches for the assessment of framing of uncertainty in water management practice, processes of communication and learning turned out to be of major importance. Making framings of uncertainties explicit by help of parameters of framing proved to be useful in the case studies for revealing different points of views on the uncertainties and with regard to the strategies to deal with them. This is a first step in enabling dialogue among opposed framers and an important precondition for reframing and learning which is crucial for the long-term performance in management of natural resources.