Parameter optimization for noise and vibration reduction associated with position and speed sensorless control of permanent magnet machines at low speed

With the advantages and popularity of Permanent Magnet (PM) motors due to their high power density, there is an increasing incentive to use them in variety of applications including electric actuation. These applications have strict noise emission standards. The generation of audible noise and associated vibration modes are characteristics of all electric motors, it is especially problematic in low speed sensorless control rotary actuation applications using high frequency voltage injection technique. This dissertation is aimed at solving the problem of optimizing the sensorless control algorithm for low noise and vibration while achieving at least 12 bit absolute accuracy for speed and position control. The low speed sensorless algorithm is simulated using an improved Phase Variable Model, developed and implemented in a hardware-in-the-loop prototyping environment. Two experimental testbeds were developed and built to test and verify the algorithm in real time.^ A neural network based modeling approach was used to predict the audible noise due to the high frequency injected carrier signal. This model was created based on noise measurements in an especially built chamber. The developed noise model is then integrated into the high frequency based sensorless control scheme so that appropriate tradeoffs and mitigation techniques can be devised. This will improve the position estimation and control performance while keeping the noise below a certain level. Genetic algorithms were used for including the noise optimization parameters into the developed control algorithm.^ A novel wavelet based filtering approach was proposed in this dissertation for the sensorless control algorithm at low speed. This novel filter was capable of extracting the position information at low values of injection voltage where conventional filters fail. This filtering approach can be used in practice to reduce the injected voltage in sensorless control algorithm resulting in significant reduction of noise and vibration.^ Online optimization of sensorless position estimation algorithm was performed to reduce vibration and to improve the position estimation performance. The results obtained are important and represent original contributions that can be helpful in choosing optimal parameters for sensorless control algorithm in many practical applications.^

Positron emission tomography (PET) tumor segmentation and quantification: Development of new algorithms

Tumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera's point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ∼10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera's PSF. The algorithm can also improve dose estimation and treatment planning.^

Combination of Evolutionary Algorithms with Experimental Design, Traditional Optimization and Machine Learning

Evolutionary algorithms alone cannot solve optimization problems very efficiently since there are many random (not very rational) decisions in these algorithms. Combination of evolutionary algorithms and other techniques have been proven to be an efficient optimization methodology. In this talk, I will explain the basic ideas of our three algorithms along this line (1): Orthogonal genetic algorithm which treats crossover/mutation as an experimental design problem, (2) Multiobjective evolutionary algorithm based on decomposition (MOEA/D) which uses decomposition techniques from traditional mathematical programming in multiobjective optimization evolutionary algorithm, and (3) Regular model based multiobjective estimation of distribution algorithms (RM-MEDA) which uses the regular property and machine learning methods for improving multiobjective evolutionary algorithms.

Positron Emission Tomography (PET) Tumor Segmentation and Quantification: Development of New Algorithms

Tumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera’s point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ~10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera’s PSF. The algorithm can also improve dose estimation and treatment planning.

Ordonnancement des opérations dans une unité d’extrusion

Les travaux de ce mémoire traitent du problème d’ordonnancement et d’optimisation de la production dans un environnement de plusieurs machines en présence de contraintes sur les ressources matérielles dans une usine d’extrusion plastique. La minimisation de la somme pondérée des retards est le critère économique autour duquel s’articule cette étude car il représente un critère très important pour le respect des délais. Dans ce mémoire, nous proposons une approche exacte via une formulation mathématique capable des donner des solutions optimales et une approche heuristique qui repose sur deux méthodes de construction de solution sérielle et parallèle et un ensemble de méthodes de recherche dans le voisinage (recuit-simulé, recherche avec tabous, GRASP et algorithme génétique) avec cinq variantes de voisinages. Pour être en totale conformité avec la réalité de l’industrie du plastique, nous avons pris en considération certaines caractéristiques très fréquentes telles que les temps de changement d’outils sur les machines lorsqu’un ordre de fabrication succède à un autre sur une machine donnée. La disponibilité des extrudeuses et des matrices d’extrusion représente le goulot d’étranglement dans ce problème d’ordonnancement. Des séries d’expérimentations basées sur des problèmes tests ont été effectuées pour évaluer la qualité de la solution obtenue avec les différents algorithmes proposés. L’analyse des résultats a démontré que les méthodes de construction de solution ne sont pas suffisantes pour assurer de bons résultats et que les méthodes de recherche dans le voisinage donnent des solutions de très bonne qualité. Le choix du voisinage est important pour raffiner la qualité de la solution obtenue. Mots-clés : ordonnancement, optimisation, extrusion, formulation mathématique, heuristique, recuit-simulé, recherche avec tabous, GRASP, algorithme génétique

Evolutionary algorithms for the modeling of bioreactors

This work aims to study the application of Genetic Algorithms in anaerobic digestion modeling, in particular when using dynamical models. Along the work, different types of bioreactors are shown, such as batch, semi-batch and continuous, as well as their mathematical modeling. The work intendeds to estimate the parameter values of two biological reaction model. For that, simulated results, where only one output variable, the produced biogas, is known, are fitted to the model results. For this reason, the problems associated with reverse optimization are studied, using some graphics that provide clues to the sensitivity and identifiability associated with the problem. Particular solutions obtained by the identifiability analysis using GENSSI and DAISY softwares are also presented. Finally, the optimization is performed using genetic algorithms. During this optimization the need to improve the convergence of genetic algorithms was felt. This need has led to the development of an adaptation of the genetic algorithms, which we called Neighbored Genetic Algorithms (NGA1 and NGA2). In order to understand if this new approach overcomes the Basic Genetic Algorithms (BGA) and achieves the proposed goals, a study of 100 full optimization runs for each situation was further developed. Results show that NGA1 and NGA2 are statistically better than BGA. However, because it was not possible to obtain consistent results, the Nealder-Mead method was used, where the initial guesses were the estimated results from GA; Algoritmos Evolucionários para a Modelação de Bioreactores Resumo: Neste trabalho procura-se estudar os algoritmos genéticos com aplicação na modelação da digestão anaeróbia e, em particular, quando se utilizam modelos dinâmicos. Ao longo do mesmo, são apresentados diferentes tipos de bioreactores, como os batch, semi-batch e contínuos, bem como a modelação matemática dos mesmos. Neste trabalho procurou-se estimar o valor dos parâmetros que constam num modelo de digestão anaeróbia para o ajustar a uma situação simulada onde apenas se conhece uma variável de output, o biogas produzido. São ainda estudados os problemas associados à optimização inversa com recurso a alguns gráficos que fornecem pistas sobre a sensibilidade e identifiacabilidade associadas ao problema da modelação da digestão anaeróbia. São ainda apresentadas soluções particulares de idenficabilidade obtidas através dos softwares GENSSI e DAISY. Finalmente é realizada a optimização do modelo com recurso aos algoritmos genéticos. No decorrer dessa optimização sentiu-se a necessidade de melhorar a convergência e, portanto, desenvolveu-se ainda uma adaptação dos algoritmos genéticos a que se deu o nome de Neighboured Genetic Algorithms (NGA1 e NGA2). No sentido de se compreender se as adaptações permitiam superar os algoritmos genéticos básicos e atingir as metas propostas, foi ainda desenvolvido um estudo em que o processo de optimização foi realizado 100 vezes para cada um dos métodos, o que permitiu concluir, estatisticamente, que os BGA foram superados pelos NGA1 e NGA2. Ainda assim, porque não foi possivel obter consistência nos resultados, foi usado o método de Nealder-Mead utilizado como estimativa inicial os resultados obtidos pelos algoritmos genéticos.

Genetic Diversity Of Giardia Duodenalis: Multilocus Genotyping Reveals Zoonotic Potential Between Clinical And Environmental Sources In A Metropolitan Region Of Brazil.

Giardia duodenalis is a flagellate protozoan that parasitizes humans and several other mammals. Protozoan contamination has been regularly documented at important environmental sites, although most of these studies were performed at the species level. There is a lack of studies that correlate environmental contamination and clinical infections in the same region. The aim of this study is to evaluate the genetic diversity of a set of clinical and environmental samples and to use the obtained data to characterize the genetic profile of the distribution of G. duodenalis and the potential for zoonotic transmission in a metropolitan region of Brazil. The genetic assemblages and subtypes of G. duodenalis isolates obtained from hospitals, a veterinary clinic, a day-care center and important environmental sites were determined via multilocus sequence-based genotyping using three unlinked gene loci. Cysts of Giardia were detected at all of the environmental sites. Mixed assemblages were detected in 25% of the total samples, and an elevated number of haplotypes was identified. The main haplotypes were shared among the groups, and new subtypes were identified at all loci. Ten multilocus genotypes were identified: 7 for assemblage A and 3 for assemblage B. There is persistent G. duodenalis contamination at important environmental sites in the city. The identified mixed assemblages likely represent mixed infections, suggesting high endemicity of Giardia in these hosts. Most Giardia isolates obtained in this study displayed zoonotic potential. The high degree of genetic diversity in the isolates obtained from both clinical and environmental samples suggests that multiple sources of infection are likely responsible for the detected contamination events. The finding that many multilocus genotypes (MLGs) and haplotypes are shared by different groups suggests that these sources of infection may be related and indicates that there is a notable risk of human infection caused by Giardia in this region.

Investigation Of Genetic Factors Underlying Typical Orofacial Clefts: Mutational Screening And Copy Number Variation.

Typical orofacial clefts (OFCs) comprise cleft lip, cleft palate and cleft lip and palate. The complex etiology has been postulated to involve chromosome rearrangements, gene mutations and environmental factors. A group of genes including IRF6, FOXE1, GLI2, MSX2, SKI, SATB2, MSX1 and FGF has been implicated in the etiology of OFCs. Recently, the role of the copy number variations (CNVs) has been studied in genetic defects and diseases. CNVs act by modifying gene expression, disrupting gene sequence or altering gene dosage. The aims of this study were to screen the above-mentioned genes and to investigate CNVs in patients with OFCs. The sample was composed of 23 unrelated individuals who were grouped according to phenotype (associated with other anomalies or isolated) and familial recurrence. New sequence variants in GLI2, MSX1 and FGF8 were detected in patients, but not in their parents, as well as in 200 control chromosomes, indicating that these were rare variants. CNV screening identified new genes that can influence OFC pathogenesis, particularly highlighting TCEB3 and KIF7, that could be further analyzed. The findings of the present study suggest that the mechanism underlying CNV associated with sequence variants may play a role in the etiology of OFC.

Genetic-morphometric variation in Culex quinquefasciatus from Brazil and La Plata, Argentina

Variation among natural populations of Culex (Culex) quinquefasciatus Say is associated with different vectorial capacities. The species Cx. quinquefasciatus is present in the equatorial, tropical and subtropical zones in the Brazilian territory, with intermediate forms between Cx. quinquefasciatus and Culex pipiens occurring in regions of latitudes around 33°-35°S. Herein, we studied geographically distinct populations of Cx. quinquefasciatus by genetic characterization and analysis of intra-specific wing morphometrics. After morphological analysis, molecular characterization of Cx. quinquefasciatus and intermediate forms was performed by polymerase chain reaction of the polymorphic nuclear region of the second intron of the acetylcholinesterase locus. Additionally, the morphology of adult female wings collected from six locations was analyzed. Wing centroid sizes were significantly different between some geographical pairs. Mean values of R2/R2+3 differed significantly after pairwise comparisons. The overall wing shape represented by morphometric characters could be divided into two main groupings. Our data suggest that Brazilian samples are morphologically and genetically distinct from the Argentinean samples and also indicated a morphological distinction between northern and southern populations of Brazilian Cx. quinquefasciatus. We suggest that wing morphology may be used for preliminary assessment of population structure of Cx. quinquefasciatusin Brazil

Additive genetic relationship of longevity with fertility and production traits in Nellore cattle based on bivariate models

Survival or longevity is an economically important trait in beef cattle. The main inconvenience for its inclusion in selection criteria is delayed recording of phenotypic data and the high computational demand for including survival in proportional hazard models. Thus, identification of a longevity-correlated trait that could be recorded early in life would be very useful for selection purposes. We estimated the genetic relationship of survival with productive and reproductive traits in Nellore cattle, including weaning weight (WW), post-weaning growth (PWG), muscularity (MUSC), scrotal circumference at 18 months (SC18), and heifer pregnancy (HP). Survival was measured in discrete time intervals and modeled through a sequential threshold model. Five independent bivariate Bayesian analyses were performed, accounting for cow survival and the five productive and reproductive traits. Posterior mean estimates for heritability (standard deviation in parentheses) were 0.55 (0.01) for WW, 0.25 (0.01) for PWG, 0.23 (0.01) for MUSC, and 0.48 (0.01) for SC18. The posterior mean estimates (95% confidence interval in parentheses) for the genetic correlation with survival were 0.16 (0.13-0.19), 0.30 (0.25-0.34), 0.31 (0.25-0.36), 0.07 (0.02-0.12), and 0.82 (0.78-0.86) for WW, PWG, MUSC, SC18, and HP, respectively. Based on the high genetic correlation and heritability (0.54) posterior mean estimates for HP, the expected progeny difference for HP can be used to select bulls for longevity, as well as for post-weaning gain and muscle score.

Parallel Dynamic Optimization of Steel Risers

This paper addresses the use of optimization techniques in the design of a steel riser. Two methods are used: the genetic algorithm, which imitates the process of natural selection, and the simulated annealing, which is based on the process of annealing of a metal. Both of them are capable of searching a given solution space for the best feasible riser configuration according to predefined criteria. Optimization issues are discussed, such as problem codification, parameter selection, definition of objective function, and restrictions. A comparison between the results obtained for economic and structural objective functions is made for a case study. Optimization method parallelization is also addressed. [DOI: 10.1115/1.4001955]

Thin titanium oxide films deposited by e-beam evaporation with additional rapid thermal oxidation and annealing for ISFET applications

Titanium oxide (TiO(2)) has been extensively applied in the medical area due to its proved biocompatibility with human cells [1]. This work presents the characterization of titanium oxide thin films as a potential dielectric to be applied in ion sensitive field-effect transistors. The films were obtained by rapid thermal oxidation and annealing (at 300, 600, 960 and 1200 degrees C) of thin titanium films of different thicknesses (5 nm, 10 nm and 20 nm) deposited by e-beam evaporation on silicon wafers. These films were analyzed as-deposited and after annealing in forming gas for 25 min by Ellipsometry, Fourier Transform Infrared Spectroscopy (FTIR), Raman Spectroscopy (RAMAN), Atomic Force Microscopy (AFM), Rutherford Backscattering Spectroscopy (RBS) and Ti-K edge X-ray Absorption Near Edge Structure (XANES). Thin film thickness, roughness, surface grain sizes, refractive indexes and oxygen concentration depend on the oxidation and annealing temperature. Structural characterization showed mainly presence of the crystalline rutile phase, however, other oxides such Ti(2)O(3), an interfacial SiO(2) layer between the dielectric and the substrate and the anatase crystalline phase of TiO(2) films were also identified. Electrical characteristics were obtained by means of I-V and C-V measured curves of Al/Si/TiO(x)/Al capacitors. These curves showed that the films had high dielectric constants between 12 and 33, interface charge density of about 10(10)/cm(2) and leakage current density between 1 and 10(-4) A/cm(2). Field-effect transistors were fabricated in order to analyze I(D) x V(DS) and log I(D) x Bias curves. Early voltage value of -1629 V, R(OUT) value of 215 M Omega and slope of 100 mV/dec were determined for the 20 nm TiO(x) film thermally treated at 960 degrees C. (C) 2009 Elsevier B.V. All rights reserved.

Genetic variation for anatomic traits and volume shrinkage and their correlation with wood basic density in an Eucalyptus camaldulensis Dehn base population

Eucalyptus camaldulensis has great importance in Brazil because of their phenotypic plasticity for different environmental conditions, as soils, altitudes and rainfall. This study is an investigation of a base population of E. camaldulensis from Australia through a progeny test implanted in Selviria, MS. The trial was established in a randomized block design, with 25 families and 60 replications of single tree plots. Genetic parameters for anatomic traits and volume shrinkage were estimated, as well as their correlations with wood basic density. No significant differences among progenies were observed for the traits studied. The additive genetic variation coefficient at individual and among progeny levels ranged from low (0.26%) to high (16.98%). The narrow sense heritability at individual and family means levels also ranged from low (0.01) to high (0.87). This indicates that some traits are under strong genetic control and can be improved by selection. In the present situation, in order to attain the highest genetic gains, the sequential selection among and within progeny would be recommended.

Analysis of small signal stability margins using genetic optimization

Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.

Role of the 6-20 disulfide bridge in the structure and activity of epidermal growth factor

Two synthetic analogues of murine epidermal. growth factor, [Abu6, 20] mEGF4-48 (where Abu denotes amino-butyric acid) and [G1, M3, K21, H40] mEGF1-48, have been investigated by NMR spectroscopy. [Abu6, 20] mEGF4-48 was designed to determine the contribution of the 6-20 disulfide bridge to the structure and function of mEGF The overall structure of this analogue was similar to that of native mEGF, indicating that the loss of the 6-20 disulfide bridge did not affect the global fold of the molecule. Significant structural differences were observed near the N-terminus, however, with the direction of the polypeptide chain between residues four and nine being altered such that these residues were now located on the opposite face of the main beta-sheet from their position in native mEGF Thermal denaturation experiments also showed that the structure of [Abu6, 20] mEGF4-48 was less stable than that of mEGF. Removal of this disulfide bridge resulted in a significant loss of both mitogenic activity in Balb/c 3T3 cells and receptor binding on A431 cells compared with native mEGF and mEGF4-48, implying that the structural changes in [Abu6, 20] mEGF4-48, although limited to the N-terminus, were sufficient to interfere with receptor binding. The loss of binding affinity probably arose mainly from steric interactions of the dislocated N-terminal region with part of the receptor binding surface of EGF [G1, M3, K21, H40] mEGF1-48 was also synthesized in order to compare the synthetic polypeptide with the corresponding product of recombinant expression. Its mitogenic activity in Balb/c 3T3 cells was similar to that of native mEGF and analysis of its H-1 chemical shifts suggested that its structure was also very similar to native.