Sliding Mode Control for Switched Mode Power Supplies

Control applications of switched mode power supplies have been widely investigated. The main objective ofresearch and development (R&D) in this field is always to find the most suitable control method to be implemented in various DC/DC converter topologies. Inother words, the goal is to select a control method capable of improving the efficiency of the converter, reducing the effect of disturbances (line and load variation), lessening the effect of EMI (electro magnetic interference), and beingless effected by component variation. The main objective of this research work is to study different control methods implemented in switched mode power supplies namely (PID control, hysteresis control, adaptive control, current programmed control, variable structure control (VSC), and sliding mode control (SMC). The advantages and drawbacks of each control method are given. Two control methods, the PID and the SMC are selected and their effects on DC/DC (Buck, Boost, and Buck-Boost) converters are examined. Matlab/SimulinkTM is used to implement PID control method in DC/DC Buck converter and SMC in DC/DC (Buck, and Buck Boost) converters. For the prototype, operational amplifiers (op-amps) are used to implement PID control in DC/DC Buck converter. For SMC op-amps are implemented in DC/DC Buck converter and dSPACETM is used to control the DC/DC Buck-Boost converter. The SMC can be applied to the DC/DC (Buck, Boost, and Buck-Boost) converters. A comparison of the effects of the PID control and the SMC on the DC/DC Buck converter response in steady state, under line variations, load variations, and different component variations is performed. Also the Conducted RF-Emissions between the PID and SMC DC/DC Buck Converter are compared. The thesis shows that, in comparison with the PID control, the SMC provides better steady-state response, better dynamic response, less EMI, inherent order reduction, robustness against system uncertainty disturbances, and an implicit stability proof. Giving a better steady-state and dynamic response, the SMC is implemented in a DC/DC resonant converter. The half-wave zero current switching (HWZCS) DC/DC Buck converter is selected as a converter topology. A general guideline to select the tank component values, needed for the designing of a HWZCS DC/DC Buck, is obtained. The implementation of the SMC to a HWZCS DC/DC Buck converter is analysed. The converter response is investigated in the steady-state region and in the dynamic region.

Active Damping and Energy Recovery in a Hydraulic Boom Controlled by an Electric Drive

The aim of the study is to obtain a mathematical description for an alternative variant of controlling a hydraulic circuit with an electrical drive. The electrical and hydraulic systems are described by basic mathematical equations. The flexibilities of the load and boom is modeled with assumed mode method. The model is achieved and proven with simulations. The controller is constructed and proven to decrease oscillations and improve the dynamic response of the system.

Varavoimalaitosten pimeäkäynnistysmahdollisuudet

Nyky yhteiskunta tulee päivä päivältä riippuvaisemmaksi sähköstä ja sen luotettavasta siirrosta ja jakelusta. Suurhäiriö kantaverkossa on erittäin epätodennäköinen, mutta sen mahdollisuutta ei koskaan voida kokonaan rajata pois. Suurhäiriön seuraukset ovat erittäin vakavat ja yhteiskäytön palautus häiriön jälkeen voi pitkittyä. Diplomityössä käsitellään kantaverkkoyhtiö Fingrid Oyj:n kaasuturpiinivaravoimalaitoksia ja niiden ominaisuuksia kantaverkon suurhäiriössä. Varavoimalaitosten pimeäkäynnistysvalmiudet tarkastettiin ja niissä suoritettiin koeajoja, jotka sisälsivät jatkuvan ja dynaamisen tilan koeajo osuudet. Yhdessä laitosyksikössä tehtiin myös pimeäkäynnistys ja saarekekoeajo. Koeajojen perusteella saatiin arvokasta perustietoa kaasuturpiinilaitosten ominaisuuksista ja mahdollisuuksista toimia pimeäkäynnistystilanteissa. Varavoimalaitosten matemaattista mallintamista yksinkertaisella teollisuuskaasuturpiinilaitoksen mallilla kokeiltiin siinä kuitenkaan onnistumatta. Kokemusten perusteella esitetään keskeisimmät havainnot ja ehdotukset kevyen, moniakselisen kaasuturpiinilaitoksen mallintamiseksi.

Salient Pole Synchronous Machine Modelling in an Industrial Direct Torque Controlled Drive Application

Synchronous motors are used mainly in large drives, for example in ship propulsion systems and in steel factories' rolling mills because of their high efficiency, high overload capacity and good performance in the field weakening range. This, however, requires an extremely good torque control system. A fast torque response and a torque accuracy are basic requirements for such a drive. For large power, high dynamic performance drives the commonly known principle of field oriented vector control has been used solely hitherto, but nowadays it is not the only way to implement such a drive. A new control method Direct Torque Control (DTC) has also emerged. The performance of such a high quality torque control as DTC in dynamically demanding industrial applications is mainly based on the accurate estimate of the various flux linkages' space vectors. Nowadays industrial motor control systems are real time applications with restricted calculation capacity. At the same time the control system requires a simple, fast calculable and reasonably accurate motor model. In this work a method to handle these problems in a Direct Torque Controlled (DTC) salient pole synchronous motor drive is proposed. A motor model which combines the induction law based "voltage model" and motor inductance parameters based "current model" is presented. The voltage model operates as a main model and is calculated at a very fast sampling rate (for example 40 kHz). The stator flux linkage calculated via integration from the stator voltages is corrected using the stator flux linkage computed from the current model. The current model acts as a supervisor that prevents only the motor stator flux linkage from drifting erroneous during longer time intervals. At very low speeds the role of the current model is emphasised but, nevertheless, the voltage model always stays the main model. At higher speeds the function of the current model correction is to act as a stabiliser of the control system. The current model contains a set of inductance parameters which must be known. The validation of the current model in steady state is not self evident. It depends on the accuracy of the saturated value of the inductances. Parameter measurement of the motor model where the supply inverter is used as a measurement signal generator is presented. This so called identification run can be performed prior to delivery or during drive commissioning. A derivation method for the inductance models used for the representation of the saturation effects is proposed. The performance of the electrically excited synchronous motor supplied with the DTC inverter is proven with experimental results. It is shown that it is possible to obtain a good static accuracy of the DTC's torque controller for an electrically excited synchronous motor. The dynamic response is fast and a new operation point is achieved without oscillation. The operation is stable throughout the speed range. The modelling of the magnetising inductance saturation is essential and cross saturation has to be considered as well. The effect of cross saturation is very significant. A DTC inverter can be used as a measuring equipment and the parameters needed for the motor model can be defined by the inverter itself. The main advantage is that the parameters defined are measured in similar magnetic operation conditions and no disagreement between the parameters will exist. The inductance models generated are adequate to meet the requirements of dynamically demanding drives.

Dynamic linkages of real estate and stock markets in Finland

Traditionally real estate has been seen as a good diversification tool for a stock portfolio due to the lower return and volatility characteristics of real estate investments. However, the diversification benefits of a multi-asset portfolio depend on how the different asset classes co-move in the short- and long-run. As the asset classes are affected by the same macroeconomic factors, interrelationships limiting the diversification benefits could exist. This master’s thesis aims to identify such dynamic linkages in the Finnish real estate and stock markets. The results are beneficial for portfolio optimization tasks as well as for policy-making. The real estate industry can be divided into direct and securitized markets. In this thesis the direct market is depicted by the Finnish housing market index. The securitized market is proxied by the Finnish all-sectors securitized real estate index and by a European residential Real Estate Investment Trust index. The stock market is depicted by OMX Helsinki Cap index. Several macroeconomic variables are incorporated as well. The methodology of this thesis is based on the Vector Autoregressive (VAR) models. The long-run dynamic linkages are studied with Johansen’s cointegration tests and the short-run interrelationships are examined with Granger-causality tests. In addition, impulse response functions and forecast error variance decomposition analyses are used for robustness checks. The results show that long-run co-movement, or cointegration, did not exist between the housing and stock markets during the sample period. This indicates diversification benefits in the long-run. However, cointegration between the stock and securitized real estate markets was identified. This indicates limited diversification benefits and shows that the listed real estate market in Finland is not matured enough to be considered a separate market from the general stock market. Moreover, while securitized real estate was shown to cointegrate with the housing market in the long-run, the two markets are still too different in their characteristics to be used as substitutes in a multi-asset portfolio. This implies that the capital intensiveness of housing investments cannot be circumvented by investing in securitized real estate.

Optimization of a dynamic district heating power plant

The purpose of this Thesis is to find the most optimal heat recovery solution for Wärtsilä’s dynamic district heating power plant considering Germany energy markets as in Germany government pays subsidies for CHP plants in order to increase its share of domestic power production to 25 % by 2020. Different heat recovery connections have been simulated dozens to be able to determine the most efficient heat recovery connections. The purpose is also to study feasibility of different heat recovery connections in the dynamic district heating power plant in the Germany markets thus taking into consideration the day ahead electricity prices, district heating network temperatures and CHP subsidies accordingly. The auxiliary cooling, dynamical operation and cost efficiency of the power plant is also investigated.

Dynamic Capabilities and Firm Performance

Firms operating in a changing environment have a need for structures and practices that provide flexibility and enable rapid response to changes. Given the challenges they face in attempts to keep up with market needs, they have to continuously improve their processes and products, and develop new products to match market requirements. Success in changing markets depends on the firm's ability to convert knowledge into innovations, and consequently their internal structures and capabilities have an important role in innovation activities. According 10 the dynamic capability view of the firm, firms thus need dynamic capabilities in (he form ofassets, processes and structures that enable strategic flexibility and support entrepreneurial opportunity sensing and exploitation. Dynamic capabilities are also needed in conditions of rapid change in the operating environment, and in activities such as new product development and expansion to new markets. Despite the growing interest in these issues and the theoretical developments in the field of strategy research, there are still only very few empirical studies, and large-scale empirical studies in particular, that provide evidence that firms'dynamic capabilities are reflected in performance differences. This thesis represents an attempt to advance the research by providing empirical evidence of thelinkages between the firm's dynamic capabilities and performance in intenationalization and innovation activities. The aim is thus to increase knowledge and enhance understanding of the organizational factors that explain interfirm performance differences. The study is in two parts. The first part is the introduction and the second part comprises five research publications covering the theoretical foundations of the dynamic capability view and subsequent empirical analyses. Quantitative research methodology is used throughout. The thesis contributes to the literature in several ways. While a lot of prior research on dynamic capabilities is conceptual in nature, or conducted through case studies, this thesis introduces empirical measures for assessing the different aspects, and uses large-scale sampling to investigate the relationships between them and performance indicators. The dynamic capability view is further developed by integrating theoretical frameworks and research traditions from several disciplines. The results of the study provide support for the basic tenets of the dynamic capability view. The empirical findings demonstrate that the firm's ability to renew its knowledge base and other intangible assets, its proactive, entrepreneurial behavior, and the structures and practices that support operational flexibility arepositively related to performance indicators.

Adaptive optimization schemes for mobile VoIP applications Battery life and call quality aspects

In this thesis programmatic, application-layer means for better energy-efficiency in the VoIP application domain are studied. The work presented concentrates on optimizations which are suitable for VoIP-implementations utilizing SIP and IEEE 802.11 technologies. Energy-saving optimizations can have an impact on perceived call quality, and thus energy-saving means are studied together with those factors affecting perceived call quality. In this thesis a general view on a topic is given. Based on theory, adaptive optimization schemes for dynamic controlling of application's operation are proposed. A runtime quality model, capable of being integrated into optimization schemes, is developed for VoIP call quality estimation. Based on proposed optimization schemes, some power consumption measurements are done to find out achievable advantages. Measurement results show that a reduction in power consumption is possible to achieve with the help of adaptive optimization schemes.

A multibody dynamic model of the cross-country ski-skating technique

The objective of this thesis is the development of a multibody dynamic model matching the observed movements of the lower limb of a skier performing the skating technique in cross-country style. During the construction of this model, the formulation of the equation of motion was made using the Euler - Lagrange approach with multipliers applied to a multibody system in three dimensions. The description of the lower limb of the skate skier and the ski was completed by employing three bodies, one representing the ski, and two representing the natural movements of the leg of the skier. The resultant system has 13 joint constraints due to the interconnection of the bodies, and four prescribed kinematic constraints to account for the movements of the leg, leaving the amount of degrees of freedom equal to one. The push-off force exerted by the skate skier was taken directly from measurements made on-site in the ski tunnel at the Vuokatti facilities (Finland) and was input into the model as a continuous function. Then, the resultant velocities and movement of the ski, center of mass of the skier, and variation of the skating angle were studied to understand the response of the model to the variation of important parameters of the skate technique. This allowed a comparison of the model results with the real movement of the skier. Further developments can be made to this model to better approximate the results to the real movement of the leg. One can achieve this by changing the constraints to include the behavior of the real leg joints and muscle actuation. As mentioned in the introduction of this thesis, a multibody dynamic model can be used to provide relevant information to ski designers and to obtain optimized results of the given variables, which athletes can use to improve their performance.

Simulation and optimization tools in paper machine concept design

The last decade has shown that the global paper industry needs new processes and products in order to reassert its position in the industry. As the paper markets in Western Europe and North America have stabilized, the competition has tightened. Along with the development of more cost-effective processes and products, new process design methods are also required to break the old molds and create new ideas. This thesis discusses the development of a process design methodology based on simulation and optimization methods. A bi-level optimization problem and a solution procedure for it are formulated and illustrated. Computational models and simulation are used to illustrate the phenomena inside a real process and mathematical optimization is exploited to find out the best process structures and control principles for the process. Dynamic process models are used inside the bi-level optimization problem, which is assumed to be dynamic and multiobjective due to the nature of papermaking processes. The numerical experiments show that the bi-level optimization approach is useful for different kinds of problems related to process design and optimization. Here, the design methodology is applied to a constrained process area of a papermaking line. However, the same methodology is applicable to all types of industrial processes, e.g., the design of biorefiners, because the methodology is totally generalized and can be easily modified.

Stability Analysis in Multicriteria Discrete Portfolio Optimization.

Almost every problem of design, planning and management in the technical and organizational systems has several conflicting goals or interests. Nowadays, multicriteria decision models represent a rapidly developing area of operation research. While solving practical optimization problems, it is necessary to take into account various kinds of uncertainty due to lack of data, inadequacy of mathematical models to real-time processes, calculation errors, etc. In practice, this uncertainty usually leads to undesirable outcomes where the solutions are very sensitive to any changes in the input parameters. An example is the investment managing. Stability analysis of multicriteria discrete optimization problems investigates how the found solutions behave in response to changes in the initial data (input parameters). This thesis is devoted to the stability analysis in the problem of selecting investment project portfolios, which are optimized by considering different types of risk and efficiency of the investment projects. The stability analysis is carried out in two approaches: qualitative and quantitative. The qualitative approach describes the behavior of solutions in conditions with small perturbations in the initial data. The stability of solutions is defined in terms of existence a neighborhood in the initial data space. Any perturbed problem from this neighborhood has stability with respect to the set of efficient solutions of the initial problem. The other approach in the stability analysis studies quantitative measures such as stability radius. This approach gives information about the limits of perturbations in the input parameters, which do not lead to changes in the set of efficient solutions. In present thesis several results were obtained including attainable bounds for the stability radii of Pareto optimal and lexicographically optimal portfolios of the investment problem with Savage's, Wald's criteria and criteria of extreme optimism. In addition, special classes of the problem when the stability radii are expressed by the formulae were indicated. Investigations were completed using different combinations of Chebyshev's, Manhattan and Hölder's metrics, which allowed monitoring input parameters perturbations differently.

Optimization and Measuring Techniques for Collect-and-Place Machines in Printed Circuit Board Industry

This thesis considers optimization problems arising in printed circuit board assembly. Especially, the case in which the electronic components of a single circuit board are placed using a single placement machine is studied. Although there is a large number of different placement machines, the use of collect-and-place -type gantry machines is discussed because of their flexibility and increasing popularity in the industry. Instead of solving the entire control optimization problem of a collect-andplace machine with a single application, the problem is divided into multiple subproblems because of its hard combinatorial nature. This dividing technique is called hierarchical decomposition. All the subproblems of the one PCB - one machine -context are described, classified and reviewed. The derived subproblems are then either solved with exact methods or new heuristic algorithms are developed and applied. The exact methods include, for example, a greedy algorithm and a solution based on dynamic programming. Some of the proposed heuristics contain constructive parts while others utilize local search or are based on frequency calculations. For the heuristics, it is made sure with comprehensive experimental tests that they are applicable and feasible. A number of quality functions will be proposed for evaluation and applied to the subproblems. In the experimental tests, artificially generated data from Markov-models and data from real-world PCB production are used. The thesis consists of an introduction and of five publications where the developed and used solution methods are described in their full detail. For all the problems stated in this thesis, the methods proposed are efficient enough to be used in the PCB assembly production in practice and are readily applicable in the PCB manufacturing industry.

The Dynamic Relationship between Finnish Stock Market and Commodities

Since different stock markets have become more integrated during 2000s, investors need new asset classes in order to gain diversification benefits. Commodities have become popular to invest in and thus it is important to examine whether the investors should use commodities as a part for portfolio diversification. This master’s thesis examines the dynamic relationship between Finnish stock market and commodities. The methodology is based on Vector Autoregressive models (VAR). The long-run relationship between Finnish stock market and commodities is examined with Johansen cointegration while short-run relationship is examined with VAR models and Granger causality test. In addition, impulse response test and forecast error variance decomposition are employed to strengthen the results of short-run relationship. The dynamic relationships might change under different market conditions. Thus, the sample period is divided into two sub-samples in order to reveal whether the dynamic relationship varies under different market conditions. The results show that Finnish stock market has stable long-run relationship with industrial metals, indicating that there would not be diversification benefits among the industrial metals. The long-run relationship between Finnish stock market and energy commodities is not as stable as the long-run relationship between Finnish stock market and industrial metals. Long-run relationship was found in the full sample period and first sub-sample which indicate less room for diversification. However, the long-run relationship disappeared in the second sub-sample which indicates diversification benefits. Long-run relationship between Finnish stock market and agricultural commodities was not found in the full sample period which indicates diversification benefits between the variables. However, long-run relationship was found from both sub-samples. The best diversification benefits would be achieved if investor invested in precious metals. No long-run relationship was found from either sample. In the full sample period OMX Helsinki had short-run relationship with most of the energy commodities and industrial metals and the causality was mostly running from equities to commodities. During the first sub period the number of short-run relationships and causality shrunk but during the crisis period the number of short-run relationships and causality increased. The most notable result found was unidirectional causality from gold to OMX Helsinki during the crisis period.

Optimization and Applications of Large-Scale Biomedical Event Networks

The overwhelming amount and unprecedented speed of publication in the biomedical domain make it difficult for life science researchers to acquire and maintain a broad view of the field and gather all information that would be relevant for their research. As a response to this problem, the BioNLP (Biomedical Natural Language Processing) community of researches has emerged and strives to assist life science researchers by developing modern natural language processing (NLP), information extraction (IE) and information retrieval (IR) methods that can be applied at large-scale, to scan the whole publicly available biomedical literature and extract and aggregate the information found within, while automatically normalizing the variability of natural language statements. Among different tasks, biomedical event extraction has received much attention within BioNLP community recently. Biomedical event extraction constitutes the identification of biological processes and interactions described in biomedical literature, and their representation as a set of recursive event structures. The 2009–2013 series of BioNLP Shared Tasks on Event Extraction have given raise to a number of event extraction systems, several of which have been applied at a large scale (the full set of PubMed abstracts and PubMed Central Open Access full text articles), leading to creation of massive biomedical event databases, each of which containing millions of events. Sinece top-ranking event extraction systems are based on machine-learning approach and are trained on the narrow-domain, carefully selected Shared Task training data, their performance drops when being faced with the topically highly varied PubMed and PubMed Central documents. Specifically, false-positive predictions by these systems lead to generation of incorrect biomolecular events which are spotted by the end-users. This thesis proposes a novel post-processing approach, utilizing a combination of supervised and unsupervised learning techniques, that can automatically identify and filter out a considerable proportion of incorrect events from large-scale event databases, thus increasing the general credibility of those databases. The second part of this thesis is dedicated to a system we developed for hypothesis generation from large-scale event databases, which is able to discover novel biomolecular interactions among genes/gene-products. We cast the hypothesis generation problem as a supervised network topology prediction, i.e predicting new edges in the network, as well as types and directions for these edges, utilizing a set of features that can be extracted from large biomedical event networks. Routine machine learning evaluation results, as well as manual evaluation results suggest that the problem is indeed learnable. This work won the Best Paper Award in The 5th International Symposium on Languages in Biology and Medicine (LBM 2013).