Rozprawy doktorskie na temat „Perturbation-Based methods”

Options are a special type of derivative securities because their values are derived from the value of some underlying security. Most options can be grouped into either of the two categories: European options which can be exercised only on the expiration date, and American options which can be exercised on or before the expiration date. American options are much harder to deal with than European ones. The reason being the optimal exercise policy of these options which led to free boundary problems. Ever since the seminal work of Black and Scholes [J. Pol. Econ. 81(3) (1973), 637-659], the differential equation approach in pricing options has attracted many researchers. Recently, numerical singular perturbation techniques have been used extensively for solving many differential equation models of sciences and engineering. In this thesis, we explore some of those methods which are based on spline approximations to solve the option pricing problems. We show a systematic construction and analysis of these methods to solve some European option problems and then extend the approach to solve problems of pricing American options as well as some exotic options. Proposed methods are analyzed for stability and convergence. Thorough numerical results are presented and compared with those seen in the literature.

In our age in which the use of electronic devices is expanding all over the world, their reliability and miniaturization have become very crucial. The thesis is based on the study of one of the most frequent failure mechanisms in semiconductor packages, the delamination of interface or the separation of two bonded materials, in order to improve their adhesion and a fortiori the reliability of microelectronic devices. It focuses on the metal (-oxide) / polymer interfaces because they cover 95% of all existing interfaces. Since several years, research activities at mesoscopic scale (1-10µm) have proved that the more roughened the surface of the interface, i.e., presenting sharp asperities, the better the adhesion between these two materials. Because roughness exhibits extremely complex shapes, it is difficult to find a description that can be used for reliability analysis of interfaces. In order to investigate quantitatively the effect of roughness variation on adhesion properties, studies have been carried out involving analytical fracture mechanics; then numerical studies were conducted with Finite Element Analysis. Both were done in a deterministic way by assuming an ideal profile which is repeated periodically. With the development of statistical and stochastic roughness representation on the one hand, and with the emergence of probabilistic fracture mechanics on the other, the present work adds a stochastic framework to the previous studies. In fact, one of the Stochastic Finite Element Methods, the Perturbation method is chosen for implementation, because it can investigate the effect of the geometric variations on the mechanical response such as displacement field. In addition, it can carry out at once what traditional Finite Element Analysis does with numerous simulations which require changing geometric parameters each time. This method is developed analytically, then numerically by implementing a module in a Finite Element package MSc. Marc/Mentat. In order to get acquainted and to validate the implementation, the Perturbation method is applied analytically and numerically to the 3 point bending test on a beam problem, because the input of the Perturbation method in terms of roughness parameters is still being studied. The capabilities and limitations of the implementation are outlined. Finally, recommendations for using the implementation and for furture work on roughness representation are discussed.

The characterization of postsynaptic potentials, in terms of neurotransmitter receptor activation, is of clinical significance because information associated with receptor activation can be used in the diagnosis and study of neurological disorders. Single-unit recordings provide a method of measuring postsynaptic potentials in neurons using a microelectrode system, but yield no detailed information regarding the neurotransmitter receptors that contribute to the potential. To determine the types of neurotransmitter receptors that result in a compound postsynaptic potential from a microelectrode reading, decomposition of the potential is necessary. In this work, a perturbation-based decomposition method developed by R. Szlavik is evaluated for this application, and compared to a generalized Fourier series approach. The resultant estimator is valid for decomposition of multiple-receptor compound postsynaptic potentials as well as single-receptor compound postsynaptic potentials. The estimator also yields a satisfactory decomposition of experimental postsynaptic potential data found in the literature.

La détection de visages à partir des images picturales du style clair-obscur suscite un intérêt croissant chez les historiens de l'art et les chercheurs afin d'estimer l'emplacement de l'illuminant et ainsi répondre à plusieurs questions techniques. L'apprentissage profond suscite un intérêt croissant en raison de ses excellentes performances. Une optimisation du Réseau "Faster Region-based Convolutional Neural Network" a démontré sa capacité à relever efficacement les défis et à fournir des résultats prometteurs en matière de détection de visages à partir des images clai-obscur. Cependant, ces réseaux sont caractérisés comme des "boites noires" en raison de la complexité inhérentes et de la non-linéarité de leurs architectures. Pour aborder ces problèmes, l'explicabilité devient un domaine de recherche actif pour comprendre les modèles profonds. Ainsi, nous proposons une nouvelle méthode d'explicabilité itérative basée sur des perturbations guidées pour expliquer les prédictions
Face detection from Tenebrism paintings is of growing interest to art historians and researchers in order to estimate the illuminant location, and thereby answer several technical questions. Deep learning is gaining increasing interest due to is high performance capabilities. An optimization of Faster Region based Convolutional Neural Network has demonstrated its ability to effectively address challenges and deliver promising face detection results from Tenebrism paintings. However, deep neural networks are often characterized as "black box" because of the inherent complexity and non-linearity of their architectures. To tackle these issues, eXplainable Artificial Intelligence (XAI) is becoming an active researcj area to understand deep models. So, we propose a novel iterative XAI method based on guided perturbations to explain model's application

Recently, a lot of research work has been dedicated toward enhancing performance, reliability and integrity of distributed energy resources that are integrated into distribution networks. The problem of islanding detection and islanding prevention (i.e. anti-islanding) has stimulated a lot of research due to its role in severely compromising the safety of working personnel and resulting in equipment damages. Various Islanding Detection Methods (IDMs) have been developed within the last ten years in anticipation of the tremendous increase in the penetration of Distributed Generation (DG) in distribution system. This work proposes new IDMs that rely on transient and distributed behaviors to improve integrity and performance of DGs while maintaining multi-DG islanding detection capability. In this thesis, the following questions have been addressed: How to utilize the transient behavior arising from an islanding condition to improve detectability and robust performance of IDMs in a distributive manner? How to reduce the negative stability impact of the well-known Sandia Frequency Shift (SFS) IDM while maintaining its islanding detection capability? How to incorporate the perturbations provided by each of DGs in such a way that the negative interference of different IDMs is minimized without the need of any type of communication among the different DGs? It is shown that the proposed techniques are local, scalable and robust against different loading conditions and topology changes. Also, the proposed techniques can successfully distinguish an islanding condition from other disturbances that may occur in power system networks. This work improves the efficiency, reliability and safety of integrated DGs, which presents a necessary advance toward making electric power grids a smart grid.
Ph.D.
Doctorate
Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering

This thesis is about using structural-dynamics based methods to address the existing challenges in the field of Structural Health Monitoring (SHM). Particularly, new structural-dynamics based methods are presented, to model areas of damage, to do damage diagnosis and to estimate and predict the sensitivity of structural vibration properties like natural frequencies to the presence of damage. Towards these objectives, a general analytical procedure, which yields nth-order expressions governing mode shapes and natural frequencies and for damaged elastic structures such as rods, beams, plates and shells of any shape is presented. Features of the procedure include the following: 1. Rather than modeling the damage as a fictitious elastic element or localized or global change in constitutive properties, it is modeled in a mathematically rigorous manner as a geometric discontinuity. 2. The inertia effect (kinetic energy), which, unlike the stiffness effect (strain energy), of the damage has been neglected by researchers, is included in it. 3. The framework is generic and is applicable to wide variety of engineering structures of different shapes with arbitrary boundary conditions which constitute self adjoint systems and also to a wide variety of damage profiles and even multiple areas of damage. To illustrate the ability of the procedure to effectively model the damage, it is applied to beams using Euler-Bernoulli and Timoshenko theories and to plates using Kirchhoff's theory, supported on different types of boundary conditions. Analytical results are compared with experiments using piezoelectric actuators and non-contact Laser-Doppler Vibrometer sensors. Next, the step of damage diagnosis is approached. Damage diagnosis is done using two methodologies. One, the modes and natural frequencies that are determined are used to formulate analytical expressions for a strain energy based damage index. Two, a new damage detection parameter are identified. Assuming the damaged structure to be a linear system, the response is expressed as the summation of the responses of the corresponding undamaged structure and the response (negative response) of the damage alone. If the second part of the response is isolated, it forms what can be regarded as the damage signature. The damage signature gives a clear indication of the damage. In this thesis, the existence of the damage signature is investigated when the damaged structure is excited at one of its natural frequencies and therefore it is called ``partial mode contribution". The second damage detection method is based on this new physical parameter as determined using the partial mode contribution. The physical reasoning is verified analytically, thereupon it is verified using finite element models and experiments. The limits of damage size that can be determined using the method are also investigated. There is no requirement of having a baseline data with this damage detection method. Since the partial mode contribution is a local parameter, it is thus very sensitive to the presence of damage. The parameter is also shown to be not affected by noise in the detection ambience.

La maintenance aéronautique est fortement régulée, notamment à travers l’établissement d’un planning de maintenance obligatoire, permettant de garantir la sureté structurale. La fréquence des arrêts en maintenance est déterminée de manière très conservative en vue d’assurer les exigences de fiabilité. Développer des stratégies de maintenance moins conservatives et plus efficaces peut alors représenter une voie pour une nouvelle croissance des compagnies aériennes. Les systèmes de monitoring embarqué de structures, sont progressivement introduits dans l’industrie aéronautique. Ces développements pourraient alors permettre de nouvelles stratégies de maintenance structurale basées sur la prévision de l’état de santé de chaque élément structural, plutôt que basée sur une maintenance programmée, tel qu’implémentée actuellement. Dans ce cadre général, ce travail se concentre sur le suivi par un système embarqué de la propagation de fissures de fatigue dans les panneaux de fuselage. Une nouvelle méthode de prévision des fissures basée sur des modèles de propagation est développée, qui permet de filtrer le bruit des mesures du système embarqué, identifier la taille actuelle de la fissure et prédire son évolution future et par conséquent la fiabilité des panneaux. Cette approche prédictive est intégrée dans le processus de maintenance structurale aéronautique et deux types de maintenances prédictives sont proposés. L’étude numérique montre que ces stratégies de maintenance prédictive peuvent réduire de manière significative les coûts de maintenance en réduisant le nombre d’arrêts en maintenance et le nombre de réparations inutiles
Aircraft maintenance represents a major economic cost for the aviation industry. Traditionally, the aircraft maintenance is highly regulated based on fixed schedules (thus called scheduled maintenance) in order to ensure safety. The frequency of scheduled maintenance is designed to be very conservative to maintain a desirable level of reliability. Developing efficient maintenance can be an important way for airlines to allow a new profit growth. With the development of sensor technology, structural health monitoring (SHM) system, which employ a sensor network sealing inside aircraft structures to monitor the damage state, are gradually being introduced in the aviation industry. Once it is possible to monitor the structure damage state automatically and continuously by SHM systems, it enables to plan the maintenance activities according to the actual or predicted health state of the aircraft rather than a fixed schedule. This work focus on the fatigue crack propagation in the fuselage panels. The SHM system is assumed to be employed. A model-based prognostics method is developed, which enables to filter the noise of SHM data to estimate the crack size, and to predict the future health state of the panels. This predictive information is integrated into the maintenance decision-making and two types of predictive maintenance are developed. The numerical study shows that the predictive maintenance significantly reduces the maintenance cost by reducing the number of maintenance stop and the repaired panels

La conception des ouvrages économiques a suscité de nombreux progrès dans les domaines de la modélisation et de l’optimisation, permettant l’analyse de structures de plus en plus complexes. Cependant, les conceptions optimisées sans considérer les incertitudes des paramètres, peuvent ne pas respecter certains critères de fiabilité. Pour assurer le bon fonctionnement de la structure, il est important de prendre en considération l’incertitude dès la phase de conception. Il existe plusieurs théories dans la littérature pour traiter les incertitudes. La théorie de la fiabilité des structures consiste à définir la probabilité de défaillance d’une structure par la probabilité que les conditions de bon fonctionnement ne soient pas respectées. On appelle cette étude l’analyse de la fiabilité. L’intégration de l’analyse de fiabilité dans les problèmes d’optimisation constitue une nouvelle discipline introduisant des critères de fiabilité dans la recherche de la configuration optimale des structures, c’est le domaine de l’optimisation fiabiliste (RBDO). Cette méthodologie de RBDO vise donc à considérer la propagation des incertitudes dans les performances mécaniques en s’appuyant sur une modélisation probabiliste des fluctuations des paramètres d’entrée. Dans ce cadre, ce travail de thèse porte sur l’analyse robuste et l’optimisation fiabiliste des problèmes mécaniques complexes. Il est important de tenir compte des paramètres incertains du système pour assurer une conception robuste. L’objectif de la méthode RBDO est de concevoir une structure afin d’établir un bon compromis entre le coût et l’assurance de fiabilité. Par conséquent, plusieurs méthodes, telles que la méthode hybride et la méthode optimum safety factor, ont été développées pour atteindre cet objectif. Pour remédier à la complexité des problèmes mécaniques complexes comportant des paramètres incertains, des méthodologies spécifiques à cette problématique, tel que les méthodes de méta-modélisation, ont été développées afin de bâtir un modèle de substitution mécanique, qui satisfait en même temps l’efficacité et la précision du modèle
The design of economic system leads to many advances in the fields of modeling and optimization, allowing the analysis of structures more and more complex. However, optimized designs can suffer from uncertain parameters that may not meet certain reliability criteria. To ensure the proper functioning of the structure, it is important to consider uncertainty study is called the reliability analysis. The integration of reliability analysis in optimization problems is a new discipline introducing reliability criteria in the search for the optimal configuration of structures, this is the domain of reliability optimization (RBDO). This RBDO methodology aims to consider the propagation of uncertainties in the mechanical performance by relying on a probabilistic modeling of input parameter fluctuations. In this context, this thesis focuses on a robust analysis and a reliability optimization of complex mechanical problems. It is important to consider the uncertain parameters of the system to ensure a robust design. The objective of the RBDO method is to design a structure in order to establish a good compromise between the cost and the reliability assurance. As a result, several methods, such as the hybrid method and the optimum safety factor method, have been developed to achieve this goal. To address the complexity of complex mechanical problems with uncertain parameters, methodologies specific to this issue, such as meta-modeling methods, have been developed to build a mechanical substitution model, which at the same time satisfies the efficiency and the precision of the model

博士
國立臺灣科技大學
電機工程系
100
The thesis is mainly to design the controller by applying the theory of singular perturbation. First of all, using the singular perturbation technique to design the output feedback controller of mechanic systems, it is similar to the design of a proportional-derivative control law. We can precede the speed control by only measuring the displacement. The controller algorithm is the rule of low-order dynamic output feedback control. It is simple and easily accomplished. Besides, when the mechanical system contains uncertain items, this thesis presents robust stability of the closed-loop system. It also offers the analysis of Lyapunov theory by solving a Riccati algebra equation and a linear matrix inequality. Furthermore, for the mismatched parameter uncertainties and matched nonlinear perturbations in a linear MIMO system, the thesis proposes a disturbance-observer based controller in which the input disturbance can be effectively estimated by using a high-gain integration observer. Finally, it is verified the practicability by numerical examples.

This thesis deals with the development of guidance laws for interceptors with seeker field-of-view (FOV) and impact angle constraints. Two classes of guidance problems, namely, field-of- view and impact angle constrained guidance; midcourse guidance of dual pulse interceptors with look angle constraints, are considered in this thesis. In the first problem, decision variables are lateral acceleration commands whereas the second problem has an additional decision variable of second thrust pulse firing time. For the first problem, three guidance laws are proposed using nonlinear control theory. These are (i) Backstepping control based guidance law (ii) Nonlinear mapping based guidance law for three dimensional engagements, and (iii) Partial integrated guidance and control based guidance law. For the second problem, singular perturbation technique is used to derive the guidance law. First, backstepping control based guidance law is proposed for impact angle and field-of-view constrained engagements in a planar geometry. The kinematic equations governing the problem are modified to strict feedback form for deriving the guidance law using backstepping technique. The look-angle, which is virtual input to the backstepping structure, is designed such that it is within the feasible domain and achieves the desired impact angle. Barrier Lyapunov functionals are used to derive a guidance law to track the virtual input without violating the field-of-view constraints. Further, capturability of the proposed guidance law is analyzed in the relative velocity plane. Simulation results are presented using a constant speed as well as a realistic interceptor model to show the efficacy of the guidance law. Next, backstepping control based guidance law is further extended to intercept targets in three dimensional space using nonlinear transformation. The interception geometry is controlled by defining impact angles in terms of flight path angles of interceptor and target. The impact angles are related to line-of-sight angles and the problem is converted to line-of-sight angle tracking problem. The state model for the control design is transformed into a new domain using tangent hyperbolic functions to handle the FOV constraints. The look angles which are constrained in the original domain are free from constraints in the transformed domain. Error surfaces are defined in the transformed domain and Lyapunov theory is used to derive the guidance law. Simulation studies performed using constant speed as well as realistic models of interceptor demonstrates the effectiveness of the proposed guidance law for three dimensional engagements. Approximations considering kinematic look angle may degrade guidance law performance. A partial integrated guidance and control (PIGC) based guidance law is proposed considering look angle without any approximations. A three dimensional engagement geometry and six degree of freedom (6-DOF) model of interceptor are used in the guidance law design. The partial integrated guidance and control uses a two loop architecture, wherein the outer loop generates body rate commands and the inner loop tracks the desired body rates by deflecting the fins. Both the loops are designed using Lyapunov theory. The look angle constraints are accounted for in the outer loop by using barrier functionals in the error surfaces. The guidance law efficiently uses the available look angle freedom to intercept the target with the desired impact angle. Simulation results using the 6-DOF model demonstrate the effectiveness of the PIGC law. Finally, Monte-Carlo studies highlight the robustness of the proposed guidance law against uncertainties in aerodynamic coefficients. In the last part of the thesis, the problem of midcourse guidance of dual pulse interceptors with look angle constraints is addressed using singular perturbation (SP) technique. This guidance law is applicable in the midcourse phase where the objective is to conserve the kinetic energy to maximize the range. This is achieved by choosing a combination of terminal velocity and flight time as a performance measure. In addition to seeker field-of-view limit, constraints in the optimization problem include minimum dynamic pressure limit arising due to aerodynamic controllability. Using the time scale separation between the state variables, the full order problem is reduced into lower order sub-problems and a closed-form solution for the guidance law is derived. It is shown that the performance of the interceptor is not very sensitive to perturbation of pulse firing time and an offline generated lookup table is used to time the second thrust pulse firing. The proposed guidance law is computationally efficient and its performance is benchmarked with that of pseudospectral based feedback guidance with much lower computational cost. Simulation studies with point mass and 6-DOF model are presented highlighting the accuracy and efficacy of the proposed guidance law.

碩士
國立交通大學
電信工程系
90
The research is based on TMN8 rate control method in H.263. We know that, theoretically, the bit allocation by TMN8 for each macroblock is proportional to the product of the deviation value and the distortion weighting . The way to find the optimized quantization value Q is to predict two parameters, K and C. Although the approach to find K and C in TMN8 results in constant frame rate, the bit allocation in each macroblock usually is not the same as the theoretical value for some reasons. Now we want to find a new approach to get K and C. By the new K and C, we will get a new optimized quantization value Q that can be used to encode the macroblock and will make the bit allocation close to the theoretical value. The parameter C is called overhead rate. In H.263 syntax, some header fields are known before rate control. We can get a new C value by finding these known fields and predicting the others. As mentioned before, the theoretical bit allocated value is usually not the same as the actual bit rate. We find the difference between the theoretical bit allocated value and the actual bit rate. According to the difference value, we update the parameter K by some algorithms. By the simulation results, we can see that the new approach to update K and C will let the actual bit rate closer to the theoretical bit allocated value. Because the new approach is still based on TMN8, we still can have constant frame rate. The benefits are getting greater PSNR and reducing skip blocks in a frame.

博士
國立交通大學
運輸與物流管理學系
103
Regression modeling has been one of the most useful and important tools for statistical research. Of all the clans in regression modeling, \emph{linear regression} refers to building a linear relationship between a set of \emph{explanatory} variables and a \emph{response} variable, enabling the researchers to examine how those explantory interact with each other and affect the responses. For instance, in econometrics, by having all other factors fixed, one can perform the \emph{ceteris peribus} analysis to examine how a unit change in a given factor affects the outcome by simply looking at the coefficient associated. Others such as biology, physics, environmental science and the likes are the related applicable fields. Thence, its wide applicability renders regression modeling an important tool for scientific studies. Linear regression is favorable in the sense that the estimation can be done by using the ordinary least squares (OLS). The theorey of OLS is so well-founded that it provides a systematic way for researchers to obtain an estimate almost automatically. In the meanwhile, supported by a rich body of statistical inference, OLS has become the core of the regression analysis. Whereas theoretically explanatory variables are assumed independent implicitly in most, if not all, linear models, the analysis proceeds with data given exogenously in practice. Usually, data are collected from a vast unknown population, encompassing certain degree of stochasticity and unpredictability, and thus problems result. For instance, an erroneous input of a data point may likely yield a completely different result for the estimates; missing data points due to certain reasons can be an obstacle for the subsequently analysis; or high similarity (dependency) in the collected data may lead to unsatisfactory results and so like. Problems of this sort are referred to as the \emph{data problems}. Of all data problems in linear regression, we are more concerned about the nearly linear dependency among several factors assumed independent implicitly in the model specification. Numerically, high dependency results directly in rank-deficiency problem in the OLS estimation. The resultant problems, such as high variance, low statistical significance, and even incorrect signs, can frustrate the researchers aiming to model a problem using the regression. Biased regression has been one of the approaches devised in the literature for solving data collinearity problems in linear regression. The most dominant method is this particular category is the ridge regression. Ridge regression has won its fame by its simplicity in implementation in practice and by producing good results. Yet, ridge regression has certain problems. First of all, by definition, the collinearity stems from the dependency between at least two different covariates in the data matrix. Instead of tackling the problem from the root, the ridge method tackles the problem by breaking the intrinsic structure of the correlation matrix, under the assumption that the data matrix is normalized. Second, the breaking the intrinsic structure leads to plausibly good results. In particular, from the persepective of VIF, the results are even infeasible, rendering also the hypothesis testings infeasible, which in turn renders the future inferences infeasible. Third, the ridge method requires a one-dimensional parameter. To find a good parameter for the ridge method, one potentially has to deal with hard optimization problem which is NP-hard in nature. Thence, to even find a local optimal, the computational effort will be quite unfriendly, let alone looking for the global oiptimality. Moreover, a simply local optimal cannot guarantee the performance of the resulting ridge estimate. Motivated by such frustrations, we aim to develope a alternative and useful method, based on the reliable diagnostic tool, to solve the commonly seen problem in the context of linear regression. The developed method is useful becasue our method inherits the merit from matrix theory and mitigates the data collinearity problem by improving not only the values of the underlying diagnostic but also the very intrinsic eigenstructure of the correlation matrix. The close connection between the diagnostic used and the correlation matrix leads to the success of our method in dealing with the problem. We carry out both the real-world applications (when they are accessible) and random instance experiments (when they are inaccessible) to validate the developed method. The success in real-world applications reveals that our method is capable of addressing realistic datasets troubled by the existence of data collinearity. Moreover, from the results of the random instance experiments, we learn that our method has more capability in dealing with arbitrarily generated (with some variabilities well controlled) datasets.

碩士
明新科技大學
電機工程研究所
101
Photovoltaic (PV) power system becomes an important alternative due to its merits such as freely available, environment friendly, and less maintenance cost. Hence, the demand of PV power system has increased. Tracking of the maximum power point （MPP） is an important and essential function of most of the PV power system. Every maximum power point tracking (MPPT) technique has its own merits and demerits, but the perturbation and observation （P&O）method is widely used because of its low cost and easy implementation. The P&O method may fail to track the exact MPP when atmospheric conditions change rapidly or the P&O method is not correctly implemented. Many improved P&O methods have been published, but most of these published techniques focus on the adjustment of the perturbation magnitude. The discussions to the effect of sampling time are seldom to be found in the corresponding literatures. Basically, the contributions of the thesis can be summarized as follows. First, a new voltage-boost dc-dc converter for PV power system is proposed, and the corresponding improved P&O method is also proposed to enhance the performance of MPPT when the solar cell module is locally operated on short circuit or open circuit. Secondly, to speed up the convergent time of the P&O method, an index is adopted to judge the steady-state operation mode. Third, a DSP-based PV power system prototype is constructed. And some experimental results are given to demonstrate the performance of the proposed improved P&O method. Finally, a LCL filter-tied grid connected PV system is simulated, and the simulated results can verify the validity.

碩士
逢甲大學
航太與系統工程所
96
Resonant cavity perturbation method is a technique to obtain the complex permittivity and permeability of bulk materials or thin films at microwave frequencies. This method uses a microwave resonant circuit to measure the shift of resonant frequency and the change of quality factor in a closed rectangular or circular waveguide. In this study, the accuracy of the resonant cavity perturbation is evaluated by changing the samples sizes and lengths of Teflon and RT/duroid. To verify the formulae used in the calculation of the complex permittivity and permeability, a numerical simulation is also carried out by using Ansoft HFSS to analyze the electromagnetic disturbance in a rectangular waveguide with an open slot for the test samples. Microwave absorbing composites are fabricated by mixing epoxy resin with carbonyl iron, nano-Fe3O4, and conductive carbon black for different weight ratios and then molded in rod shapes. Using the resonant perturbation method, these microwave absorbing composites are measured in X-band and compared with the transmission/reflection method by using a coaxial line. The results show either complex permittivity or permeability of these two methods are rather consistent. The discrepancy becomes large for high permittivity materials. This research provides a simple and reliable method to measure the electromagnetic properties of materials in the microwave frequency range and may benefit the development of new microwave materials and microwave devices.

碩士
國立雲林科技大學
電子與光電工程研究所碩士班
100
This thesis presents a novel algorithm for tracking maximum power points (MPPs) for a photovoltaic (PV) system. The algorithm which combines a lookup table (LUT) method and a perturbation and observation (P&O) method can quickly and accurately track the MPPs. The LUT method makes the operating points close to MPPs by the linear relationship between the current at the MPPs and the short circuit current. And then the P&O method is adopted to obtain the MPPs. The data of LUT will be updated from the MPPs obtained by the P&O method. Therefore, the proposed method which does not require additional sensor can solve the problems when the system gets old or the data of lookup table has errors. The novel algorithm which is easy to implement does not require the knowledge or specification of PV arrays, and it can work on stand-alone systems or grid-connected systems. The proposed maximum power point tracking controller has been verified with a boost converter by using a digital signal processor (TMS320LF2812).

A hybrid design optimization method combining the stochastic method based on simultaneous perturbation stochastic approximation (SPSA) and the deterministic method of Broydon-Fletcher-Goldfarb-Shanno (BFGS) is developed in order to take advantage of the high efficiency of the gradient based methods and the global search capabilities of SPSA for applications in the optimal aerodynamic shape design of a three dimensional elliptic nozzle. The performance of this hybrid method is compared with that of SPSA, simulated annealing (SA) and gradient based BFGS method. The objective functions which are minimized are estimated by numerically solving the 3D Euler and Navier-Stokes equations using a TVD approach and a LU implicit scheme. Computed results show that the hybrid optimization method proposed in this study shows a promise of high computational efficiency and global search capabilities.
Singapore-MIT Alliance (SMA)