The linear source-filter model (LSFM) has been used as a primary model for speech processing since 1960 when G. Fant presented acoustic speech production theory. It assumes that the source of voiced speech sounds, glottal flow, is independent of the filter, vocal tract. However, acoustic simulations based on the physical speech production models show that, especially when the fundamental frequency (F0) of source harmonics approaches to the first formant frequency (F1) of vocal tract filter, the filter has significant effects on the source due to the nonlinear coupling between them. In this thesis, as an alternative to linear source-filter model, nonlinear interactive source-filter models are proposed for voiced speech. This thesis has two parts, in the first part, a framework for the coupling of the source and the filter is presented. Then, two interactive system models are proposed assuming that glottal flow is a quasi-steady Bernoulli flow and acoustics in vocal tract is linear. In these models, instead of glottal flow, glottal area is used as a source for voiced speech. In the proposed interactive models, the relation between the glottal flow, glottal area and vocal tract is determined by the quasi-steady Bernoulli flow equation. It is theoretically shown that linear source-filter model is an approximation of the nonlinear models. Estimation of ISFM&rsquo / s parameters from only speech signal is a nonlinear blind deconvolution problem. The problem is solved by a robust method developed based on the acoustical interpretation of the systems. Experimental results show that ISFMs produce source-filter coupling effects seen in the physical simulations and the parameter estimation method produce always stable and better performing models than LSFM model. In addition, a framework for the incorporation of the source-filter interaction into classical source-filter model is presented. The Rosenberg source model is extended to an interactive source for voiced speech and its performance is evaluated on a large speech database. The results of the experiments conducted on vowels in the database show that the interactive Rosenberg model is always better than its noninteractive version. In the second part of the thesis, LSFM and ISFMs are compared by using not only the speech signal but also HSV (High Speed Endocopic Video) of vocal folds in a system identification approach. In this case, HSV and speech are used as a reference input-output data for the analysis and comparison of the models. First, a new robust HSV processing algorithm is developed and applied on HSV images to extract the glottal area. Then, system parameters are estimated by using a modified version of the method proposed in the first part. The experimental results show that speech signal can contain some harmonics of the fundamental frequency of the glottal area other than those contained in the glottal area signal. Proposed nonlinear interactive source-filter models can generate harmonics components in speech and produce more realistic speech sounds than LSFM.

Aging infrastructure and personnel, combined with stricter financial constraints has put maintenance, or more popular Asset Management, at the top of the agenda for most power utilities. At the same time the industry reports that this area is not properly supported by information systems. Today’s power utilities have very comprehensive and complex portfolios of information systems that serve many different purposes. A common problem in such heterogeneous system architectures is data management, e.g. data in the systems do not represent the true status of the equipment in the power grid or several sources of data are contradictory. The research presented in this thesis concerns how this industrial problem can be better understood and approached by novel use of the ontology standardized in the Common Information Model defined in IEC standards 61970 & 61968. The theoretical framework for the research is that of data management using ontology based frameworks. This notion is not new, but is receiving renewed attention due to emerging technologies, e.g. Service Oriented Architectures, that support implementation of such ontological frameworks. The work presented is empirical in nature and takes its origin in the ontology available in the Common Information Model. The scope of the research is the applicability of the CIM ontology, not as it was intended i.e. in systems integration, but for analysis of business processes, legacy systems and data. The work has involved significant interaction with power distribution utilities in Sweden, in order to validate the framework developed around the CIM ontology. Results from the research have been published continuously, this thesis consists of an introduction and summary and papers describing the main contribution of the work. The main contribution of the work presented in this thesis is the validation of the proposition to use the CIM ontology as a basis for analysis existing legacy systems. By using the data models defined in the standards and combining them with established modeling techniques we propose a framework for information system management. The framework is appropriate for analyzing data quality problems related to power systems maintenance at power distribution utilities. As part of validating the results, the proposed framework has been applied in a case study involving medium voltage overhead line inspection. In addition to the main contribution, a classification of the state of the practice system support for power system maintenance at utilities has been created. Second, the work includes an analysis and classification of how high performance Wide Area communication technologies can be used to improve power system maintenance including improving data quality. / QC 20100614

Photovoltaic installations in urban areas operate under uneven lighting conditions. For such a system to achieve its peak efficiency, each solar panel is connected in series through a micro-converter, a dc-dc converter that performs per-panel distributed maximum power point tracking (DMPPT). The objective of this thesis is to design a compensator for the DMPPT micro-converter. A novel, systematic approach to plant modeling is presented for this system, together with a framework for characterizing the plant’s uncertainty. A robust control design procedure based on linear matrix inequalities is then proposed, which ensures robust performance and stability of the time-varying system. The proposed modeling and control design methods are demonstrated for an example rooftop photovoltaic installation. The system and the designed compensator are tested in simulations. Simulation results show satisfactory performance over a range of operating conditions, and the simulated system is shown to track the maximum power point of every panel.

Photovoltaic installations in urban areas operate under uneven lighting conditions. For such a system to achieve its peak efficiency, each solar panel is connected in series through a micro-converter, a dc-dc converter that performs per-panel distributed maximum power point tracking (DMPPT). The objective of this thesis is to design a compensator for the DMPPT micro-converter. A novel, systematic approach to plant modeling is presented for this system, together with a framework for characterizing the plant’s uncertainty. A robust control design procedure based on linear matrix inequalities is then proposed, which ensures robust performance and stability of the time-varying system. The proposed modeling and control design methods are demonstrated for an example rooftop photovoltaic installation. The system and the designed compensator are tested in simulations. Simulation results show satisfactory performance over a range of operating conditions, and the simulated system is shown to track the maximum power point of every panel.

Neuro-fuzzy modeling is an efficient computing paradigm for system modeling problems. It mainly integrates two well-known approaches, neural networks and fuzzy systems, and therefore possesses advantages of them, i.e., learning capability, robustness, human-like reasoning, and high understandability. Up to now, many approaches have been proposed for neuro-fuzzy modeling. However, it still exists many problems need to be solved. We propose in this thesis two self-constructing rule generation methods, i.e., similarity-based rule generation (SRG) and similarity-and-merge-based rule generation (SMRG), and one hybrid learning algorithm (HLA) for structure identification and parameter identification, respectively, of neuro-fuzzy modeling. SRG and SMRG group the input-output training data into a set of fuzzy clusters incrementally based on similarity tests on the input and output spaces. Membership functions associated with each cluster are defined according to statistical means and deviations of the data points included in the cluster. Additionally, SMRG employs a merging mechanism to merge similar clusters dynamically. Then a zero-order or first-order TSK-type fuzzy IF-THEN rule is extracted from each cluster to form an initial fuzzy rule-base which can be directly employed for fuzzy reasoning or be further refined in the next phase of parameter identification. Compared with other methods, both our SRG and SMRG have advantages of generating fuzzy rules quickly, matching membership functions closely with the real distribution of the training data points, and avoiding the generation of the whole set of clusters from the scratch when new training data are considered. Besides, SMRG supports a more reasonable and quick mechanism for cluster merging to alleviate the problems of data-input-order bias and redundant clusters, which are encountered in SRG and other incremental clustering approaches. To refine the fuzzy rules obtained in the structure identification phase, a zero-order or first-order TSK-type fuzzy neural network is constructed accordingly in the parameter identification phase. Then, we develop a HLA composed by a recursive SVD-based least squares estimator and the gradient descent method to train the network. Our HLA has the advantage of alleviating the local minimal problem. Besides, it learns faster, consumes less memory, and produces lower approximation errors than other methods. To verify the practicability of our approaches, we apply them to the applications of function approximation and classification. For function approximation, we apply our approaches to model several nonlinear functions and real cases from measured input-output datasets. For classification, our approaches are applied to a problem of human object segmentation. A fuzzy self-clustering algorithm is used to divide the base frame of a video stream into a set of segments which are then categorized as foreground or background based on a combination of multiple criteria. Then, human objects in the base frame and the remaining frames of the video stream are precisely located by a fuzzy neural network which is constructed with the fuzzy rules previously obtained and is trained by our proposed HLA. Experimental results show that our approaches can improve the accuracy of human object identification in video streams and work well even when the human object presents no significant motion in an image sequence.

This thesis aims to propose multiple methods for performing a hardware-in-the-loop simulation, providing the hardware and software tools necessary for design and execution. For this purpose, methods of modeling commonly encountered dynamical system components are explored and techniques suitable for calculating the states of the modeled system are presented. Modules and subsystems that enable the realization of a hardware-in-the-loop simulation application and its interfacing with external controller hardware are explained. The thesis also presents three different simulation scenarios. Solutions suitable for these scenarios are provided along with their implementations. The details and specifications of the developed software packages and hardware platforms are given. The provided results illustrate the advantages and disadvantages of the approaches used in these solutions.

The Turkish TSO (TEIAS) has been leading a project that aims the synchronous interconnected operation of the Turkish Power System and the ENTSO-E CESA (former UCTE) System. For this purpose, this study concentrates on the specific problems related to the electromechanical systems of large size hydroelectric power plants regarding low frequency inter area oscillations, which are prone to occur once the interconnected operation is established. The expected frequency of inter area oscillations after interconnected operation is close to 0.15 Hz, which is in the frequency range of the speed governing structures of turbines, as explained in the first two sections of the thesis. In the third section, the nonlinear turbine governor model used throughout the study is explained. In the following part, the governor parameter tuning study with regard to the defined performance objectives is explained. Afterwards, the effect of the retuned governor settings of the sample hydroelectric power plants on a simple multi machine power system is shown. Following that, the system wide effect of removing the sources of negative damping, which are strongly dependent on the governor settings of the major hydroelectric power plants of the Turkish Power System, is shown. In the final part, conclusions are made on the operation of the hydroelectric power plants regarding the frequency stability of the system after synchronous interconnected operation of the Turkish Power System and the ENTSO-E CESA System.

Shortage of drinking water in most parts of the world has been a growing concern in recent times. The situation has been getting worse in underdeveloped and developing countries due to sudden explosion in population growth and the growth in the industries. The natural resources for potable water are limited and unless a feasible solution is obtained in the near future, the ‘concern situation’ may turn into a ‘panic situation’. A possible solution for the shortage in drinking water is to use water from inexhaustible sources such as oceans and seas and make it potable using desalination process. However, the process of desalination is an energy intensive process which the poor countries can not afford. In recent times, the cost of fossil fuels has been skyrocketing. With the crude oil costing more than Rs.5200 (US$120) a barrel as on September 2008, even the rich countries like USA and the countries in the European Union are feeling the pinch of the energy cost. Alternate energy sources such as solar, wind, geo-thermal, hydrogen etc., have become the order of the day. These sources are renewable and are environmental friendly. More than one third of the populations of the world live in coastal areas. These areas get abundant amount of solar energy throughout the year. Utilization of this energy in desalination process would solve drinking water problem to a very great extent. However, construction of centralized desalination plants requires large amount of capital which the poor countries can ill-afford. An alternate solution would be to construct decentralized smaller plants that would require smaller capital to construct and easier to maintain. If the energy requirement is tapped from renewable sources such as solar, then the operational cost also becomes affordable for the poor countries. By taking care of the water requirement of the coastal areas through this process, one may save large amounts of money in transporting potable water from interior areas to the coastal areas. There would be enough water for the people living in the interior areas. The water bed level in the interior areas would gradually increase, thereby reducing the drinking water concerns significantly. In this thesis, a small scale stand alone power generation system for the desalination process is proposed that is suitable to provide clean potable water from sources such as sea water or brackish water. Solar energy is proposed as a source of energy for the proposed desalination system. This source is available in plenty in arid and semi-arid areas. It is free and is also friendlier to the environment. It is proposed to use solar energy in thermal form to obtain energy equivalent of ‘latent heat of vaporization’ for the vaporization process and in electrical form for operating the dc machines and electronic control units that are integral parts of the desalination system. The proposed desalination unit can be built as small as possible even to feed a single household’s requirement and hence can be conceptualized as decentralized units. These units would require considerably less capital to build, and would require minimum maintenance. The desalination process is based on flash evaporation wherein a heated liquid is subjected to a pressure reduction by passing through a throttling device resulting in an initially superheated state. In the proposed desalination process, the traditional flash evaporator is extended to include continuous dynamic pressure modulation to obtain an optimal flow rate for a specified energy input. The cost function or the performance index for optimization is defined as the ratio of flow rate to the energy spent. The optimal flow rate occurs at a specific chamber pressure for a given inlet water temperature. By operating at optimal pressure, significant energy is saved for a specific flow rate. This principle is validated experimentally and the results are presented and discussed in the thesis. This proposed scheme along with hybrid energy input will prove to be an attractive solution for community drinking water problem. A system needs to have a mathematical representation in order to predict the dynamic behavior of the system. This thesis proposes the bond graph method of modeling the physical system wherein the energy flow across the electrical, thermal and the hydraulic domains are included. A system may comprise of several subsystems and the energy flow in each subsystem may be in a different domain. A desalination system is such a system wherein the energy flow in subsystems is in different domains such as electrical, thermal and hydraulics. The bond graph approach is best suited for modeling of such systems where the power/energy flow across domains can be easily and seamlessly integrated. The thesis proposes a fifth order dynamic model of a single stage flash evaporation with pressure modulation using the bond graph approach. The proposed model incorporates the effects of chamber pressure variation, the entropy flow from the chamber due to conduction, convection, radiation and also the thermal dynamics of the water bodies in the evaporation, condensation and collection chambers. The proposed model is simulated in MATLAB/Simulink environment. The simulation results are compared with the experimental results to validate the model. This proposed model can be used for both analysis and synthesis of a desalination system. The desalination system is a complex system wherein multiple energy domains are involved. The thesis presents a systematic process for the design of the desalination system. Design of the desalination system involves design of multi domain subsystems. The design becomes much more complex if the energy source to run the system is solar/ hybrid solar based. The energy budget has to be carefully evaluated considering the worst case conditions for the availability of solar energy. Hence, the information on the quantum of solar energy available at any location is a critical parameter needed for design of the desalination system. A generic method of developing a solar insolation model for a specific region such as the Indian sub-continent is proposed in this thesis along with the validation of the model by comparing measured value with the values that are obtained from the model. As the insolation model is dependent on the water vapor content in the vertical column at the location, the methodology is further applied to develop a model for estimating the precipitated water vapor content in a vertical column for any location. The model is validated by comparing the computed values to the measured values. The thesis further presents the design and selection of the balance of the system. The selection of the balance of the system includes sizing of solar thermal plate collectors such as flat plate for pre-heating and paraboloid for vaporization, solar PV panels for operating pumps, actuator and control units, and battery for backup source for night loads and during ‘no-sun days’, criteria of selecting centrifugal pump for circulating condensation water, vacuum pump for dynamic pressure modulation and selecting linear actuator for Sun tracking of the paraboloid concentrator. A discussion on the electronic circuits used in the control scheme is presented in this thesis. This includes the circuit for maximum power point tracking, circuit for DC-DC conversion, circuit for pressure modulation, circuit for speed control of linear actuator, and finally the circuit for water level limiter. A discussion on the life cycle costing is also presented in this thesis. This is an important parameter that refers to the accumulated worth of all the costs related to building and operating the desalination plant during its life span. It is emphasized that the objective of the design process is to minimize the life cycle cost while meeting other performance requirements. Thus, life cycle costing is an essential part of the design cycle. The design methodology and the approach used to design the desalination system are implemented in the form of a toolbox in the MATLAB environment. The various functions of the toolbox are highlighted by a detailed step by step presentation of the design modules in the thesis. The modules form the components of the design toolbox for designing the proposed desalination system.

Rising energy demand, fossil fuel costs, and greenhouse gas emissions have led to a growing interest in renewable energy integration. Remote communities, often accompanied by high energy costs and abundant renewable energy resources, are ideal cases for renewable energy integration. The Queen Charlotte Islands, also known as Haida Gwaii, are a remote archipelago off the northwest coast of British Columbia, Canada that relies heavily on diesel fuel for energy generation. An investigation is done into the potential for electricity generation using both tidal stream and wave energy in Haida Gwaii. A mixed integer optimization network model is developed in a Matlab and GAMS software environment, subject to set of system constraints including minimum operational levels and transmission capacities. The unit commitment and economic dispatch decisions are dynamically solved for four periods of 336 hours, representing the four annual seasons. Optimization results are used to develop an operational strategy simulation model, indicative of realistic operator behaviour. Results from both models find that the tidal stream energy resource in Haida Gwaii has a larger potential to reduce energy costs than wave energy; however, tidal steam energy is more difficult to integrate from a system operation point of view and, in the absence of storage, would only be practical at power penetration levels less than 20%.

Aus der Einleitung: "Innovative interdisziplinäre Produktentwicklung erfordert ein Überdenken von heutigen Methoden, Prozessen, IT-Lösungen und Organisationsformen. Insbesondere fehlt es an Unterstützung durch geeignete IT-Lösungen für die funktionale Beschreibung und Auslegung von Systemarchitekturen. Für die disziplinübergreifende Systemmodellierung der Konzeptphase gibt es nur eingeschränkte IT-Unterstützung. Elektronik und Software stellen einen immer stärkeren Anteil im Produktentwicklungsprozess (PEP) dar. Konstruktions- und Entwurfsmethoden dieser Disziplinen sollten auf den Prüfstand gestellt und ihre Tauglichkeit für einen moderne interdisziplinären Konstruktionsansatz überprüft werden. Model Based Systems Engineering (MBSE) könnte sich als integrative Methode etablieren und eine Brücke zwischen den verschiedenen Ingenieurdisziplinen bilden. Als »Enabler« für das MBSE werden Systemmodellierungssprachen wie z.B. SysML vorgestellt, die ein Werkzeug für eine interdisziplinäre Systembeschreibung darstellen. Auf konkreterer Stufe können Simulationssprachen, wie z.B. Matlab/Simulink oder Modelica eine frühe multidisziplinäre Simulation ermöglichen, die in Verbindung mit Systembeschreibungssprachen eine frühe Konzeptformulierung erlauben. Dieser Beitrag soll neue Methoden, Prozesse und IT-Lösungen für eine interdisziplinäre virtuelle Produktentwicklung aufzeigen (Anderl et al. 2012)."