This thesis is broadly concerned with online-optimizing anti-windup control. These are control structures that implement some online-optimization routines to compensate for the windup effects in constrained control systems. The first part of this thesis examines a general framework for analyzing robust preservation in anti-windup control systems. This framework - the robust Kalman conjecture - is defined for the robust Lur’e problem. This part of the thesis verifies this conjecture for first-order plants perturbed by various norm-bounded unstructured uncertainties. Integral quadratic constraint theory is exploited to classify the appropriate stability multipliers required for verification in these cases. The remaining part of the thesis focusses on accelerated gradient methods. In particular, tight complexity-certificates can be obtained for the Nesterov gradient method, which makes it attractive for implementation of online-optimizing anti-windup control. This part of the thesis presents a proposed algorithm that extends the classical Nesterov gradient method by using available secant information. Numerical results demonstrating the efficiency of the proposed algorithm are analysed with the aid of performance profiles. As the objective function becomes more ill-conditioned, the proposed algorithm becomes significantly more efficient than the classical Nesterov gradient method. The improved performance bodes well for online-optimization anti-windup control since ill-conditioning is common place in constrained control systems. In addition, this thesis explores another subcategory of accelerated gradient methods known as Barzilai-Borwein gradient methods. Here, two algorithms that modify the Barzilai-Borwein gradient method are proposed. Global convergence of the proposed algorithms for all convex functions is established by using discrete Lyapunov theorems.

<div>The objective of this doctoral research was to develop a versatile inverse heat transfer approach, that would enable the solution of small scale problems present in microelectronics, as well as the analysis of the complex heat flux in turbines. An inverse method is a mathematical approach which allows the resolution of problems starting from the solution. In a direct problem, the boundary conditions are given, and using the governing physics principles and equations you can calculate the solution or physical effect. In an inverse method, the solution is provided and through the physical equations, the boundary conditions can be determined. Therefore, the inverse method applied to heat transfer means that we know the variation of temperature (effect) over time and space. With the temperature input, the geometry, thermal properties of the test article and the heat diffusion equation, we can compute the spatially- and temporally-varying heat flux that generated the temperature map.</div><div><br></div><div>This doctoral dissertation develops two inverse methodologies: (1) an optimization methodology based on the conjugate gradient method and (2) a function specification method combined with a regularization technique, which is less robust but much faster. We implement these methodologies with commercial codes for solving conductive heat transfer with COMSOL and for conjugate heat transfer with ANSYS Fluent.</div><div><br></div><div>The goal is not only the development of the methods but also the validation of the techniques in two different fields with a common purpose: quantifying heat dissipation. The inverse methods were applied in the micro-scale to the dissipation of heat in microelectronics and in the macro-scale to the gas turbine engines.<br></div><div><br></div><div>In microelectronics, we performed numerical and experimental studies of the two developed inverse methodologies. The intent was to predict where heat is being dissipated and localized hot spots inside of the chip from limited measurements of the temperature outside of the chip. Here, infrared thermography of the chip surface is the input to the inverse methods leveraging thermal model of the chip. Furthermore, we combined the inverse methodology with a Kriging interpolation technique with genetic algorithm optimization to optimize the location and number of the temperature sensors inside of the chip required to accurately predict the thermal behavior of the microchip at each moment of time and everywhere.<br></div><div><br></div><div>In the application for gas turbine engines, the inverse method can be useful to detect or predict the conditions inside of the turbine by taking measurements in the outer casing. Therefore, the objective is the experimental validation of the technique in a wind tunnel especially designed with optical access for non-contact measurement techniques. We measured the temperature of the outer casing of the turbine rotor with an infrared camera and surface temperature sensors and this information is the input of the two methodologies developed in order to predict which the heat flux through the turbine casing. A new facility, specifically, an annular turbine cascade, was designed to be able to measure the relative frame of the rotor from the absolute frame. In order to get valuable data of the heat flux in a real engine, we need to replicate the Mach, Reynolds, and temperature ratios between fluid and solid. Therefore, the facility can reproduce a large range of pressures and flow temperatures. Because some regions of interest are not accessible, this researchprovides a significant benefit for understanding the system performance from limited data. With inverse methods, we can measure the outside of objects and provide an accurate prediction of the behavior of the complete system. This information is relevant not only for new designs of gas turbines or microchips, but also for old designs where due to lack of prevision there are not enough sensors to monitor the thermal behavior of the studied system.<br></div><div><br></div>

The Method of Moments (MoM) has been used extensively to solve electromagnetic problems. Its popularity is largely attributed to its adaptability to structures with various shapes and success in predicting the equivalent induced currents accurately. However, due to its dense matrix, especially for large structures, the MoM suffers from long matrix solution time and large storage requirement. In this thesis it is shown that use of wavelet basis functions result in a MoM matrix which is sparser than the one obtained by using traditional basis functions. A new wavelet system, different from the ones found in literature, is proposed. Stabilized Bi-Conjugate Gradient Method which is an iterative matrix solution method is utilized to solve the resulting sparse matrix equation. Both a one-dimensional problem with a microstrip line example and a two-dimensional problem with a rectangular patch antenna example are studied and the results are compared.

<p>This dissertation focuses on a FFT based forward EM solver and its application in inverse problems. The main contributions of this work are two folded. On the one hand, it presents the first scaled lab experiment system in the oil and gas industry for through casing hydraulic fracture evaluation. This system is established to validate the feasibility of contrasts enhanced fractures evaluation. On the other hand, this work proposes a FFT based VIE solver for hydraulic fracture evaluation. This efficient solver is needed for numerical analysis of such problem. The solver is then generalized to accommodate scattering simulations for anisotropic inhomogeneous magnetodielectric objects. The inverse problem on anisotropic objects are also studied.</p><p>Before going into details of specific applications, some background knowledge is presented. This dissertation starts with an introduction to inverse problems. Then algorithms for forward and inverse problems are discussed. The discussion on forward problem focuses on the VIE formulation and a frequency domain solver. Discussion on inverse problems focuses on iterative methods.</p><p>The rest of the dissertation is organized by the two categories of inverse problems, namely the inverse source problem and the inverse scattering problem. </p><p>The inverse source problem is studied via an application in microelectronics. In this application, a FFT based inverse source solver is applied to process near field data obtained by near field scanners. Examples show that, with the help of this inverse source solver, the resolution of unknown current source images on a device under test is greatly improved. Due to the improvement in resolution, more flexibility is given to the near field scan system.</p><p>Both the forward and inverse solver for inverse scattering problems are studied in detail. As a forward solver for inverse scattering problems, a fast FFT based method for solving VIE of magnetodielectric objects with large electromagnetic contrasts are presented due to the increasing interest in contrasts enhanced full wave EM imaging. This newly developed VIE solver assigns different basis functions of different orders to expand flux densities and vector potentials. Thus, it is called the mixed ordered BCGS-FFT method. The mixed order BCGS-FFT method maintains benefits of high order basis functions for VIE while keeping correct boundary conditions for flux densities and vector potentials. Examples show that this method has an excellent performance on both isotropic and anisotropic objects with high contrasts. Examples also verify that this method is valid in both high and low frequencies. Based on the mixed order BCGS-FFT method, an inverse scattering solver for anisotropic objects is studied. The inverse solver is formulated and solved by the variational born iterative method. An example given in this section shows a successful inversion on an anisotropic magnetodielectric object. </p><p>Finally, a lab scale hydraulic fractures evaluation system for oil/gas reservoir based on previous discussed inverse solver is presented. This system has been setup to verify the numerical results obtained from previously described inverse solvers. These scaled experiments verify the accuracy of the forward solver as well as the performance of the inverse solver. Examples show that the inverse scattering model is able to evaluate contrasts enhanced hydraulic fractures in a shale formation. Furthermore, this system, for the first time in the oil and gas industry, verifies that hydraulic fractures can be imaged through a metallic casing.</p> / Dissertation

Orientador: Edevar Luvizotto Junior / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Civil, Arquitetura e Urbanismo / Made available in DSpace on 2018-08-11T21:41:10Z (GMT). No. of bitstreams: 1 Anjo_LuizFernandoResendedosSantos_D.pdf: 3588080 bytes, checksum: 122271523488dc8a40a0d509bd1b0cf8 (MD5) Previous issue date: 2008 / Resumo: Este texto descreve as etapas que objetivam a utilização da estrutura originalmenteproposta por Todini e Pilati no chamado método gradiente (MG), utilizado para análise em regime permanente em instalações a condutos forçados, na formulação de um modelo dinâmico inercial rígido (MDIR), para a análise de escoamentos transitórios lentos neste tipo de instalação. São apresentadas as bases teóricas para esta nova modelação, justificadas através do equacionamento geral do escoamento fluido em condutos forçados. Os resultados obtidos pelo MDIR são comparados com os resultados obtidos pelo programa EPANET que utiliza o método gradiente. Discussões a respeito da importância da incorporação do efeito de inércia são apresentadas através de um estudo de casos, no caso de modelação hidráulica, e para análises de qualidade decorrentes desta. / Abstract: This research describes the stages which aim the use of the original structure proposed by Todini and Pilati in the so called gradient method (GM), used in the analysis in steady state of pipe networks, in the formulation of an inertial rigid dynamic model (IRDM) to analyse slow transients in this type of installation. The theoretical bases are presented for this new method, justified by the general equation of fluids flow in pipes networks. The results obtained by the MDIR are compared to the results obtained in the EPANET program, which uses the gradient method. Discussion on the importance of the incorporation of the inertia effect are presented through a study case of hydraulic modelation and for quality analysis which derived from it. / Doutorado / Recursos Hidricos / Doutor em Engenharia Civil

Submitted by Jaqueline Silva (jtas29@gmail.com) on 2016-09-12T20:46:48Z No. of bitstreams: 2 Dissertação - Abssan Matuzinhos de Moura - 2016.pdf: 1317960 bytes, checksum: d406a9bf2b4d0bbca0ad6e3b52da498d (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Jaqueline Silva (jtas29@gmail.com) on 2016-09-12T20:47:11Z (GMT) No. of bitstreams: 2 Dissertação - Abssan Matuzinhos de Moura - 2016.pdf: 1317960 bytes, checksum: d406a9bf2b4d0bbca0ad6e3b52da498d (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2016-09-12T20:47:11Z (GMT). No. of bitstreams: 2 Dissertação - Abssan Matuzinhos de Moura - 2016.pdf: 1317960 bytes, checksum: d406a9bf2b4d0bbca0ad6e3b52da498d (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-04-29 / The gradient method is a classical optimization methods to minimize a function. This method deserves special mention for its simplicity and easy understanding. This work is based on the study of the gradient method with step size given by the variant Barzilai- Borwein. Our goal is to present the convergence of the method with this variant. First we will study the two-dimensional case, for strictly convex quadratic functions. In this case, besides obtaining the convergence of the method, we see that such convergence occurs with R-superlinear rate. In the final part of the work, we will study the method with the variant Barzilai-Borwein not necessarily quadratic functions, concluding that the method converges. / O Método Gradiente é um dos métodos clássicos de otimização para minimizar uma função. Esse método merece um destaque especial pela sua simplicidade e fácil compreensão. Este trabalho se baseia no estudo do Método Gradiente com tamanho do passo dado pela variante de Barzilai-Borwein. Nosso objetivo é apresentar a convergência do método com esta variante. Primeiro faremos o estudo no caso bidimensional, para funções quadráticas estritamente convexas. Neste caso, além de obtermos a convergência do método, veremos que tal convergência ocorre com taxa R-superlinear. Na parte final do trabalho, faremos o estudo do método com a variante de Barzilai-Borwein para funções não necessariamente quadráticas, concluindo que o método converge.

This paper proposes new iterative methods for the efficient computation of the smallest eigenvalue of the symmetric nonlinear matrix eigenvalue problems of large order with a monotone dependence on the spectral parameter. Monotone nonlinear eigenvalue problems for differential equations have important applications in mechanics and physics. The discretization of these eigenvalue problems leads to ill-conditioned nonlinear eigenvalue problems with very large sparse matrices monotone depending on the spectral parameter. To compute the smallest eigenvalue of large matrix nonlinear eigenvalue problem, we suggest preconditioned iterative methods: preconditioned simple iteration method, preconditioned steepest descent method, and preconditioned conjugate gradient method. These methods use only matrix-vector multiplications, preconditioner-vector multiplications, linear operations with vectors and inner products of vectors. We investigate the convergence and derive grid-independent error estimates of these methods for computing eigenvalues. Numerical experiments demonstrate practical effectiveness of the proposed methods for a class of mechanical problems.

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X-ray computed tomography (CT) holds a critical role in current medical practice for the evaluation of patients, particularly in the emergency department and intensive care units. Expensive high resolution stationary scanners are available in radiology departments of most hospitals. In many situations however, a small, inexpensive, portable CT unit would be of significant value. Several mobile or miniature CT scanners are available, but none of these systems have the range, flexibility or overall physical characteristics of a truly portable device. The main challenge is the design of a geometry that optimally trades image quality for system size. The goal of this work has been to develop analysis tools to help simulate and evaluate novel system geometries. To test the tools we have developed, three geometries have been considered in the thesis, namely, parallel projections, clam-shell and parallel plate geometries. The parallel projections geometry is commonly used in reconstruction of images by filtered back projection technique. A clam-shell structure consists of two semi-cylindrical braces that fold together over the patient's body and connect at the top. A parallel plate structure uses two fixed flat or curved plates on either side of the patient's body and image from fixed sources/detectors that are gated on and off so as to step the X-ray field through the body. The parallel plate geometry has been found to be the least reliable of the three geometries investigated, with the parallel projections geometry being the most reliable. For the targeted application, the clam-shell geometry seems to be the solution with more chances to succeed in the short term. We implemented the Van Cittert iterative technique for the reconstruction of images from projections. The thesis discusses a number of variations on the algorithm, such as the use of the Conjugate Gradient Method, several choices for the initial guess, and the incorporation of a priori information to handle the reconstruction of images with metal inserts.

In this thesis, optimization approaches for intensity-modulated radiation therapy are developed and evaluated with focus on numerical efficiency and treatment delivery aspects. The first two papers deal with strategies for solving fluence map optimization problems efficiently while avoiding solutions with jagged fluence profiles. The last two papers concern optimization of step-and-shoot parameters with emphasis on generating treatment plans that can be delivered efficiently and accurately. In the first paper, the problem dimension of a fluence map optimization problem is reduced through a spectral decomposition of the Hessian of the objective function. The weights of the eigenvectors corresponding to the p largest eigenvalues are introduced as optimization variables, and the impact on the solution of varying p is studied. Including only a few eigenvector weights results in faster initial decrease of the objective value, but with an inferior solution, compared to optimization of the bixel weights. An approach combining eigenvector weights and bixel weights produces improved solutions, but at the expense of the pre-computational time for the spectral decomposition. So-called iterative regularization is performed on fluence map optimization problems in the second paper. The idea is to find regular solutions by utilizing an optimization method that is able to find near-optimal solutions with non-jagged fluence profiles in few iterations. The suitability of a quasi-Newton sequential quadratic programming method is demonstrated by comparing the treatment quality of deliverable step-and-shoot plans, generated through leaf sequencing with a fixed number of segments, for different number of bixel-weight iterations. A conclusion is that over-optimization of the fluence map optimization problem prior to leaf sequencing should be avoided. An approach for dynamically generating multileaf collimator segments using a column generation approach combined with optimization of segment shapes and weights is presented in the third paper. Numerical results demonstrate that the adjustment of leaf positions improves the plan quality and that satisfactory treatment plans are found with few segments. The method provides a tool for exploring the trade-off between plan quality and treatment complexity by generating a sequence of deliverable plans of increasing quality. The final paper is devoted to understanding the ability of the column generation approach in the third paper to find near-optimal solutions with very few columns compared to the problem dimension. The impact of different restrictions on the generated columns is studied, both in terms of numerical behaviour and convergence properties. A bound on the two-norm of the columns results in the conjugate-gradient method. Numerical results indicate that the appealing properties of the conjugate-gradient method on ill-conditioned problems are inherited in the column generation approach of the third paper. / QC 20100709