In order to design robust controllers, H-infinity synthesis is a common tool to use. The controllers that result from these algorithms are typically of very high order, which complicates implementation. However, if a constraint on the maximum order of the controller is set, that is lower than the order of the plant, the problem is no longer convex and it is then relatively hard to solve. These problems become very complex, even when the order of the system to be controlled is low. The approach used in the thesis is based on formulating the constraint on the maximum order of the plant as a polynomial equation. By using the fact that the polynomial is non-negative on the feasible set, the problem is reformulated as an optimization problem where the nonconvex polynomial function is to be minimized over a convex set defined by linear matrix inequalities. To solve this optimization problem, two methods have been proposed. The first method is a barrier method and the second one is a method based on a primal-dual framework. These methods have been evaluated on several problems and compared with a well-known method found in the literature. To motivate this choice of method, we have made a brief survey of available methods available for solving the same or related problems. The proposed methods emerged as the best methods among the three for finding lower order controllers with the same or similar performance as the full order controller. When the aim is to find the lowest order controller with no worse than +50% increase in the closed loop H-infinity norm, then the three compared methods perform equally well.

Studies have shown that linguistic and perceptual constraints are important for speech processing. First, rule-like structures are more easily learned over vowels than over consonants. Second, sequences varying in pitch and duration are grouped following the Iambic – Trochaic Law (ITL). In this research, I investigated the origins of these linguistic and perceptual constraints. My aim was to test if vowels’ acoustic saliency was the reason why they are the preferred target for abstract computations, and to explore the extent to which the principles of the ITL come from evolutionary heritage or language experience. Results show that rats learn rules over consonants and vowels with the same ease, so saliency is insufficient to explain the asymmetries observed in humans. This also shows that animals share with humans the trochaic principle of the ITL, but they lack the iambic-grouping bias, which might rely on language experience. / Diversos estudios han encontrado que limitaciones perceptuales y de aprendizaje intervienen en el procesamiento del lenguaje. Primero, que el aprendizaje de reglas se realiza mejor sobre las vocales. Segundo, que secuencias alternando en frecuencia y duración son agrupadas siguiendo la Ley Yámbico-Trocaico (LYT). En esta investigación busqué esclarecer el origen de estas limitaciones lingüísticas y perceptuales. Mi objetivo fue estudiar si la preferencia por las vocales se debe a su prominencia acústica e investigar hasta qué punto la LYT es producto de la herencia evolutiva o de la experiencia lingüística. Los resultados muestran que las ratas computan reglas sobre vocales y consonantes, por lo que las asimetrías funcionales observadas en humanos no se explican por la saliencia acústica de las vocales. También sugieren que animales y humanos comparten el principio trocaico de la LYT, pero no el yámbico, el cual podría emerger tras años de experiencia con el lenguaje nativo.

Introduction: A general guideline was introduced on October first 2010 regarding a mortgage cap, limiting the degree of leverage of housing as collateral. Through the new guidelines the marked conditions concerning consumers’ choice of mortgage has changed. The consumers are limited in the sense that they can’t only use mortgage when purchasing a house. In this context there is a higher burden on the consumers in different aspects. In this study we intend to investigate how the consumers’ conditions affect choice of financing option when buying a home. Purpose: The study aims to highlight how consumers situation affect the choice of financing option. Furthermore, the study intends to describe the consumer’s choice of financing. That is how the consumer approaches the purchase with the mortgage cap of 85 per cent. Method: For the study, we have used a quantitative research method. The starting point has been a deductive study, where we from theory collect empirical data. In the collection of empirical data we used a convenience sample. Theory: The study’s frame of reference includes a description of the financing options that consumers can use. Further, how the decision-making process appears in the choice of financing a house purchase as well as how socio-demographic factors; age, income and family affect the process and choice of financing. Conclusion: The study shows that age and income are the two socio-demographic factorsthat have the greatest impact on consumer choice of option in the decision-makingprocess. Further, data from the study shows that mortgage and own savings are the mostrecurring funding option that consumers use. In the use of private loans, we see thatconsumers’ families have a great influence, since the majority have received private loansfrom their parents. Similar relationship can be seen in the usage of guarantor. Forunsecured debt, we see that the use is concentrated among younger consumers.

IEEE P1687 (IJTAG) is proposed to add more exibility|compared with IEEE 1149.1 JTAG|for accessing on-chip embedded test features called instruments. This exibility makes it possible to include and exclude instruments from the scan path. To reach a minimal test time, all instruments should be accessed concurrently. However, constraints such as power and resource constraints might limit concurrency. There is a need to consider power and resource constraints while developing the test schedule. This thesis consists of two parts. In the rst part, three test time calculation approaches, namely session-based test schedule with a xed scan path, session-based test schedule with a recongurable scan path, and session-less test schedule with a recongurable scan path are proposed. In the second part, three test scheduling approaches, namely session-based test scheduling, optimized session-based test scheduling, and optimized session-less test scheduling are studied and three algorithms are presented for each of the test scheduling approaches. Experiments are carried out using the test scheduling approaches and the results show that optimized sessionless test scheduling can signicantly reduce the test time compared with session-based test scheduling.

The conceptualization of leisure constraints is dependent on negotiating a hierarchy of intrapersonal, interpersonal, and structural leisure constraints. It has become a recognizable and distinct subfield within leisure studies. Research has shown that the leisure constraints should not be necessarily viewed as insurmountable obstacles. Individuals can negotiate constraints by applying an array of coping mechanisms. Recently, Iwasaki and Schneider (2003) and Schneider and Stanis (2007) proposed that constraints negotiation and coping with stress share much in common. Leisure constraints are considered elements of stress, whereas constraint negotiation appears to share commonalities with ways of coping with stress. The distinction between negotiation and coping is that negotiation is something people have engaged in prior to participating in the activity, whereas coping involves strategies people more typically engage in during active participation (in response to unwanted or unanticipated situations). Based on past literature, I constructed a constraints-coping model to extend our understanding of constraints negotiation by integrating an understanding of coping mechanisms into leisure constraints-negotiation models. In order to broaden the scope of a constraints-coping framework, I integrated additional social indicators (e.g., commitment, motivation, place attachment, and frequency of participation) into my hypothesized model. First, my testing of the constraints-coping model provided empirical support for Iwasaki and his colleagues' suggestion that coping strategies can be potentially integrated into models of constraints-negotiation processes. Second, I confirmed that the three types of onsite constraints continue to have relevance for active participants. The three types of constraining factors directly influence subsequent aspects of leisure engagement for recreationists already participating. Third, I confirmed that recreationists are more likely to cope with constraints by employing an array of problem-focused coping strategies, rather than to simply adjust cognitively. However, my findings illustrate that recreationists' coping responses vary in response to different types of constraints encountered (e.g., intrapersonal, interpersonal, and structural). The experience of constraints did not universally result in the increased use of coping. Fourth, my results confirm that motivation is an immediate antecedent of constraints as well as a potential trigger for encouraging more problem-focused coping strategies. Last, four selected key variables (e.g., place attachment, commitment motivation, and frequency of participation) demonstrated different effects on influencing active participants' perceived constraints and subsequent coping strategies. Future investigations of coping strategies should continue to explore how active participants cope with onsite constraints based on a constraints-coping model in different settings.

<p>Aircrafttrajectory optimization is traditionally used forminimizing fuel consumption or time when going from one flightstate to another. This thesis presents a possible approach toincorporate tactical constraints in aircraft trajectoryoptimization.</p><p>The stealth technology of today focuses on making thetactics already in use more effective. Since tactics andstealth are closely interrelated, new and better results may beobtained if both aspects are considered simultaneously. Simplyreducing the radar cross section area in some directionswithout considering tactical aspects may result in little, ifany, improvement.</p><p>Flight tests have been performed in cooperation withEricsson Microwave Systems and the Swedish Air Force FlightAcademy. The aircraft used was the subsonic jet trainer Saab105, designated SK60 by the Swedish Air Force. The results showa decrease of 40% in the time interval between the instant theaircraft was first detected until it could pass above the radarstation. This corresponds to a reduced radar cross section(RCS) in the direction from the aircraft to the radar of almost90%, if classical RCS reduction techniques would have beenapplied.</p><p>If a modern aircraft with stealth properties would be used,the proposed methodology is believed to increase the possibleimprovements further. This is because the variation of themagnitude of RCS in different directions is greater for a shapeoptimized aircraft, which is the property exploited by thedeveloped method.</p><p>The methods presented are indeed an approach utilizing theideas of the network centric warfare (NCW) concept. Themethodology presented depends on accurate information about theadversary, while also providing up-to-date information to theother users in the information network.</p><p>The thesis focuses on aircraft but the methods are generaland may be adapted for missiles, shipsor land vehicles. Theproposed methods are also economically viable since they areuseful for existing platforms without costly modifications. Themethods presented are not limited to radar threats only. Thereasons for using radar in this thesis are the availablenon-classified data and that radar is known to pose a majorthreat against aircraft.</p>

A pilot study by Subramanian et al. on Markov decision problem task decomposition by humans revealed that participants break down tasks into both short-term subgoals with a defined end-condition (such as "go to food") and long-term considerations and invariants with no end-condition (such as "avoid predators"). In the context of Markov decision problems, behaviors having clear start and end conditions are well-modeled by an abstraction known as options, but no abstraction exists in the literature for continuous constraints imposed on the agent's behavior. We propose two representations to fill this gap: the state constraint (a set or predicate identifying states that the agent should avoid) and the state-action constraint (identifying state-action pairs that should not be taken). State-action constraints can be directly utilized by an agent, which must choose an action in each state, while state constraints require an approximation of the MDP’s state transition function to be used; however, it is important to support both representations, as certain constraints may be more easily expressed in terms of one as compared to the other, and users may conceive of rules in either form. Using domains inspired by classic video games, this dissertation demonstrates the thesis that explicitly modeling this negative policy information improves reinforcement learning performance by decreasing the amount of training needed to achieve a given level of performance. In particular, we will show that even the use of negative policy information captured from individuals with no background in artificial intelligence yields improved performance. We also demonstrate that the use of options and constraints together form a powerful combination: an option and constraint can be taken together to construct a constrained option, which terminates in any situation where the original option would violate a constraint. In this way, a naive option defined to perform well in a best-case scenario may still accelerate learning in domains where the best-case scenario is not guaranteed.

Fatigue, or failure of material due to repeated cyclic loading, is one of the most common causes of mechanical failures. The risk of fatigue in a load carrying component is often lowered by adding material, thereby reducing stresses. This increases the component weight, reducing the performance of the component and increasing its manufacturing cost. There is thus a need to design components to be as light as possible, while keeping the risk of fatigue at a low enough level, i.e. there is a need for optimization of the component subject to fatigue constraints.  This thesis deals with design against fatigue using topology optimization, which is a form of structural optimization where an optimal design is sought by using mathematical programming to decide which parts of a design domain should be filled with material, and which should not.  To predict fatigue, accurate representation of the geometry and accurate stress computation are of utmost importance. In this thesis, methods for imposing constraints such as minimum inner radii and minimum member sizes in the form of four new density filters are proposed. The filters are able to generate a very sharp representation of the structural boundary. A method for improving the accuracy of stress results at the structural boundary is also proposed, based on extrapolation of results from the interior of the structure. The method gives more accurate stresses, which affects the resulting structures when solving optimization problems.  A formulation for fatigue constraints in topology optimization is proposed, based on the weakest link integral. The formulation avoids the problem of choosing between accurate but costly local constraints, and efficient but approximate aggregated constraints, and gives a theoretical motivation for using expressions similar to the p-norm of stresses.  For verifying calculations of the fatigue probability of an optimized structure, critical plane criteria are commonly used. A new method for evaluating such criteria using optimization methods is proposed, and is proved to give results within a user given error tolerance. It is shown that compared to existing brute force methods, the proposed method evaluates significantly fewer planes in the search of the critical one. / <p>QC 20150504</p>

Most studies view transaction costs and constraints separate in the mean-variance framework. As such, I evaluate the benefits of holding and turnover constraints in the presence of transaction costs on Swedish Asset Returns. In theory, the benefits should be limited when transaction costs are included in the portfolio rebalancing problem. By using the model developed by Mitchell and Braun (2003), my results indicate that there are benefits of holding constraints in the mean-variance optimization. The main issue with the long-only portfolio is its lack of diversification. The strategy allocates the majority of the investment in 15 out of 100 assets. By imposing holding constraints, the portfolio becomes more diversified while reducing turnover volume and increasing Sharpe ratio. I find that the homogenous 1/N holding constraint increases monthly Sharpe ratio performance by 50 percent over the entire sample. However, the results are not consistent over all samples and not statistically significant. Further, turnover constraints only marginally increase performance, which more likely originates from the increase in diversification.

Topology optimization is commonly used to distribute a given amount of material to obtain the stiffest structure, with predefined fixed loads. The present work investigates the result of applying stress constraints to topology optimization, for problems with design-depending loading, such as self-weight and pressure. In order to apply pressure loading, a material boundary identification scheme is proposed, iteratively connecting points of equal density. In previous research, design-dependent loading problems have been limited to compliance minimization. The present study employs a more practical approach by minimizing mass subject to failure constraints, and uses a stress relaxation technique to avoid stress constraint singularities. The results show that these design dependent loading problems may converge to a local minimum when stress constraints are enforced. Comparisons between compliance minimization solutions and stress-constrained solutions are also given. The resulting topologies of these two solutions are usually vastly different, demonstrating the need for stress-constrained topology optimization.