The problem addressed in this research is the in-flight generation of trajectories for autonomous unmanned aircraft, which requires a method of generating pseudo-optimal trajectories in near-real-time, on-board the aircraft, and without external intervention. The focus of this research is the enhancement of a particular inverse dynamics direct method that is a candidate solution to the problem. This research introduces the following contributions to the method. A quaternion-based inverse dynamics model is introduced that represents all orientations without singularities, permits smooth interpolation of orientations, and generates more accurate controls than the previous Euler-angle model. Algorithmic modifications are introduced that: overcome singularities arising from parameterization and discretization; combine analytic and finite difference expressions to improve the accuracy of controls and constraints; remove roll ill-conditioning when the normal load factor is near zero, and extend the method to handle negative-g orientations. It is also shown in this research that quadratic interpolation improves the accuracy and speed of constraint evaluation. The method is known to lead to a multimodal constrained nonlinear optimization problem. The performance of the method with four nonlinear programming algorithms was investigated: a differential evolution algorithm was found to be capable of over 99% successful convergence, to generate solutions with better optimality than the quasi- Newton and derivative-free algorithms against which it was tested, but to be up to an order of magnitude slower than those algorithms. The effects of the degree and form of polynomial airspeed parameterization on optimization performance were investigated, and results were obtained that quantify the achievable optimality as a function of the parameterization degree. Overall, it was found that the method is a potentially viable method of on-board near- real-time trajectory generation for unmanned aircraft but for this potential to be realized in practice further improvements in computational speed are desirable. Candidate optimization strategies are identified for future research.

Student Number : 0214677F - PhD thesis - School of Camputational and Applied Mathematics - Faculty of Science / Many real-life problems are formulated as global optimization problems with continuous variables. These problems are in most cases nonsmooth, nonconvex and often simulation based, making gradient based methods impossible to be used to solve them. Therefore, ef#2;cient, reliable and derivative-free global optimization methods for solving such problems are needed. In this thesis, we focus on improving the ef#2;ciency and reliability of some global optimization methods. In particular, we concentrate on improving some population set-based methods for unconstrained global optimization, mainly through hybridization. Hybridization has widely been recognized to be one of the most attractive areas of unconstrained global optimization. Experiments have shown that through hybridization, new methods that inherit the strength of the original elements but not their weakness can be formed. We suggest a number of new hybridized population set-based methods based on differential evolution (de), controlled random search (crs2) and real coded genetic algorithm (ga). We propose #2;ve new versions of de. In the #2;rst version, we introduce a localization, called random localization, in the mutation phase of de. In the second version, we propose a localization in the acceptance phase of de. In the third version, we form a de hybrid algorithm by probabilistically combining the point generation scheme of crs2 with that of de in the de algorithm. The fourth and #2;fth versions are also de hybrids. These versions hybridize the mutation of de with the point generation rule of the electromagnetism-like (em) algorithm. We also propose #2;ve new versions of crs2. The #2;rst version modi#2;es the point generation scheme of crs2 by introducing a local mutation technique. In the second and third modi#2;cations, we probabilistically combine the point generation scheme of crs2 with the linear interpolation scheme of a trust-region based method. The fourth version is a crs hybrid that probabilistically combines the quadratic interpolation scheme with the linear interpolation scheme in crs2. In the #2;fth version, we form a crs2 hybrid algorithm by probabilistically combining the point generation scheme of crs2 with that of de in the crs2 algorithm. Finally, we propose #2;ve new versions of the real coded genetic algorithm (ga) with arithmetic crossover. In the #2;rst version of ga, we introduce a local technique. We propose, in the second version, an integrated crossover rule that generates two children at a time using two different crossover rules. We introduce a local technique in the second version to obtain the third version. The fourth and #2;fth versions are based on the probabilistic adaptation of crossover rules. The ef#2;ciency and reliability of the new methods are evaluated through numerical experiments using a large test suite of both simple and dif#2;cult problems from the literature. Results indicate that the new hybrids are much better than their original counterparts both in reliability and ef#2;ciency. Therefore, the new hybrids proposed in this study offer an alternative to many currently available stochastic algorithms for solving global optimization problems in which the gradient information is not readily available.

O processo fermentativo para a obtenção de etanol constitui um sistema complexo. Durante a fermentação se desenvolvem infecções em forma crônica e os surtos de infecção aguda aparecem em condições que; por causa da dinâmica não-linear do processo que envolve uma rede de reações metabólicas dos microrganismos, a alta dependência às condições de contorno e pelas interações sinérgicas e antagônicas envolvidas neste ecossistema; ainda representam um tema relevante de pesquisa em aberto. O presente trabalho propõe contribuir na tarefa de interpretar tais efeitos por intermédio de um modelo que inclua a interferência das bactérias. É proposto um cenário em escala laboratorial e controlado com a linhagem isolada de Saccharomyces cerevisiae PE-2 em co-cultura com bactérias de metabolismo heterofermentativo e homofermentativo. A interferência é explicada por intermédio de um modelo com efeito fixo baseado em um modelo não estruturado proposto por Lee (1983), e modificado a partir dos estudos de Andrietta (2003). São conduzidos ensaios de quatro tratamentos: uma fermentação controle e outras contaminadas com cada um dos diferentes tipos de bactérias e também em conjunto, a fim de fornecer dados experimentais para ajuste do modelo em discussão. Em seguida, são realizadas estimativas dos parâmetros que compõem as equações diferenciais da cinética da fermentação, utilizando um algoritmo genético baseado em evolução diferencial Storn e Price (1997). Completa-se a avaliação dos parâmetros por intermédio da análise de sensibilidade paramétrica dos mesmos. De posse desses resultados, é utilizado o modelo do tratamento controle como base, e são inseridos vetores de variáveis categóricas, correspondentes a efeitos fixos. Tais variáveis permitem modelar a interferência da contaminação no modelo matemático proposto. A estatística descritiva, a análise utilizando inferência bayesiana e a interpretação bioquímica dos resultados complementam as inferências obtidas a respeito do modelo. A análise de sensibilidade e correlação dos parâmetros, mostrou que os modelos para a cinética da fermentação, estudados e bem conhecidos não são adequados para modelar o processo, pela alta correlação dos seus parâmetros. O tratamento controle teve um rendimento de 46,97% na produção de etanol, o tratamento com bactéria heterofermentativa teve uma redução de 2.35% e com a mistura de ambas a redução foi de 1,58%. Uma das principais contribuições deste estudo relacionasse à produção de glicerol, o resultado mostra que no há impacto significativo na presença de bactérias homofermentativas e sim uma clara tendência a inibir a sua produção. Apresentam-se também indícios de sinergia entre as bactérias e de consumo de manitol pela bactéria homofermentativa. / The fermentation process for obtaining ethanol is a complex system. During fermentation develop chronic infections and outbreaks of acute infection in conditions that appear, because of the nonlinear dynamics of the process that involves a network of metabolic reactions of microorganisms, the high dependence on boundary conditions and the synergistic interactions and antagonistic involved in this ecosystem, still represent a relevant topic of research open. This paper proposes to contribute in the interpreting such effects through a model that includes the interference of bacteria. We propose a scenario in laboratory scale and controlled with the strain isolated from Saccharomyces cerevisiae PE-2 in co-culture with bacteria and homofermentativo heterofermentative metabolism. The interference is explained by means of a template with fixed effect based on a non structured proposed by Lee (1983) and modified from studies Andrietta (2003). Tests are conducted four treatments: a control fermentation and other contaminated with each of the different bacteria and also in conjunction in order to provide experimental data to fit the model under discussion. Are then carried estimates of the parameters that make up the differential equations of the kinetics of the fermentation, using a genetic algorithm based on differential evolution Storm and Price (1997). To complete the parameters evaluated through analysis of the same parameter sensitivity. With these results, the model is used as the basis of the control treatment, and are inserted vectors of categorical variables, corresponding to fixed effects. These variables allow modeling the interference of contamination in the mathematical model. Descriptive statistics and Bayesian inference analysis and interpretation of biochemical results obtained complement inferences about the model. Sensitivity analysis and correlation of parameters for the models showed that the kinetics of the fermentation, well studied and known are not suitable for modeling the process, the high correlation between the parameters. The control had a yield of 46.97% in ethanol, treatment with heterofermentative bacteria was reduced by 2.35% and a mixture of both reduction was 1.58%. A major contribution of this study is related to the glycerol, the result shows that no significant impact on the presence of homofermentative bacteria but a clear tendency to inhibit their production. It also presents evidence of synergy between bacteria and consumption of mannitol by homofermentative bacteria.

Submitted by ALEXANDRE ATAÍDE CARNIATO null (carniato@ifsp.edu.br) on 2017-02-13T14:14:35Z No. of bitstreams: 1 tese_ALEXANDRE_CARNIATO.pdf: 2485892 bytes, checksum: 0939b36770a8ff339e05b2e899308da3 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2017-02-16T16:48:25Z (GMT) No. of bitstreams: 1 caniato_aa_dr_ilha.pdf: 2485892 bytes, checksum: 0939b36770a8ff339e05b2e899308da3 (MD5) / Made available in DSpace on 2017-02-16T16:48:25Z (GMT). No. of bitstreams: 1 caniato_aa_dr_ilha.pdf: 2485892 bytes, checksum: 0939b36770a8ff339e05b2e899308da3 (MD5) Previous issue date: 2016-12-16 / Este trabalho examina o problema de controle robusto aplicado a sistemas lineares chaveados contínuos no tempo através de uma estratégia de chaveamento dependente apenas da saída medida da planta. Em implementações de sistemas de controle com alocação de polos, o vetor de estado pode não estar completamente disponível. Deste modo, é importante desenvolver estratégias de chaveamento que dependam da saída medida da planta. Inicialmente são propostas novas condições de estabilidade para sistemas lineares chaveados com incertezas politópicas através de uma estratégia de chaveamento adequada. Posteriormente considera-se também o chaveamento de realimentações estáticas da saída. Além disto, considera-se a inserção de um critério de desempenho, neste caso, um custo garantido para sistemas chaveados. Variáveis de folga são acrescentadas nas condições de teoremas dispostos na literatura visando reduzir o conservadorismo das desigualdades matriciais lineares. Em sequência, definindo um sistema aumentado interpretando-se a saída medida da planta como uma nova variável de estado do sistema, são propostas condições originais para a estabilidade que podem reduzir o conservadorismo de técnicas conhecidas. No que tange à realimentação dinâmica de saída, condições de estabilidade e desempenho foram propostas considerando filtros dinâmicos alocados em série com a saída medida da planta. Em seguida, apresentam-se condições para o projeto de controladores robustos estáticos/dinâmicos de saída utilizando-se equações matriciais lineares. Nesta etapa, além da regra de chaveamento, os controladores robustos são responsáveis por garantir estabilidade assintótica e um desempenho adequado. Adicionalmente são propostas novas condições de estabilidade e desempenho para sistemas lineares chaveados incertos considerando que a matriz de entrada é incerta, porém invariante no tempo. Porém, tais condições são representadas por desigualdades matriciais bilineares. Para a obtenção de soluções factíveis para este problema, utilizou-se o método híbrido Differential Evolution - Linear Matrix Inequalities (DELMI), que é baseado em um algoritmo evolutivo e também em um solver de LMIs. Análises teóricas e exemplos numéricos de simulação mostram que as técnicas de controle propostas são eficazes e menos conservadoras do que procedimentos similares disponíveis na literatura. O procedimento proposto pode também ser usado para projetar controladores robustos para plantas com incertezas e sujeitas a falhas estruturais, considerando as incertezas da planta e as falhas estruturais como incertezas politópicas. Um exemplo ilustra a potencialidade do método por meio da aplicação prática no projeto e implementação de um controlador robusto para um sistema de suspensão ativa sujeito a falhas estruturais.

Feeder reconfiguration is performed by changing the open/close status of two types of switches: normally open tie switches and normally closed sectionalizing switches. A whole feeder or part of a feeder may be served from another feeder by closing a tie switch linking the two while an appropriate sectionalizing switch must be opened to maintain the radial structure of the system. Feeder reconfiguration is mainly aiming to reduce the system overall power losses and improve voltage profile. In this dissertation, several approaches have been proposed to reconfigure the radial distribution networks including the potential impact of integrating Distributed Energy Resources (DER) into the grid. These approaches provide a Fast-Genetic Algorithm “FGA” in which the size and convergence speed is improved compared to the conventional genetic algorithm. The size of the population matrix is also smaller because of the simple way of constructing the meshed network. Additionally, FGA deals with integer variable instead of a binary one, which makes FGA a unique method. The number of the mesh/loop is based on the number of tie switches in a particular network. The validity of the proposed FGA is investigated by comparing the obtained results with the one obtained from the most recent approaches. The second the approach is the implementation of the Differential Evolution (DE) algorithm. DE is a population-based method using three operators including crossover, mutation, and selection. It differs from GA in that genetic algorithms rely on crossover while DE relies on mutation. Mutation is based on the differences between randomly sampled pairs of solutions in the population. DE has three advantages: the ability to find the global optimal result regardless of the initial values, fast convergence, and requirement of a few control parameters. DE is a well-known and straightforward population-based probabilistic approach for comprehensive optimization. In distribution systems, if a utility company has the right to control the location and size of distributed generations, then the location and size of DGs may be determined based on some optimization methods. This research provides a promising approach to finding the optimal size and location of the planned DER units using the proposed DE algorithm. DGs location is obtained using the sensitivity of power losses with respect to real power injection at each bus. Then the most sensitive bus is selected for installing the DG unit. Because the integration of the DG adds positive real power injections, the optimal location is the one with the most negative sensitivity in order to get the largest power loss reduction. Finally, after the location is specified, the proposed Differential Evolution Algorithm (DEA) is used to obtain the optimal size of the DG unit. Only the feasible solutions that satisfy all the constraints are considered. The objective of installing DG units to the distribution network is to reduce the system losses and enhance the network voltage profile. Nowadays, these renewable DGs are required to equip with reactive power devices (such as static VAR compensators, capacitor banks, etc.), to provide reactive power as well as to control the voltage at their terminal bus. DGs have various technical benefits such as voltage profile improvement, relief in feeder loading, power loss minimization, stability improvement, and voltage deviation mitigation. The distributed generation may not achieve its full potential of benefits if placed at any random location in the system. It is necessary to investigate and determine the optimum location and size of the DG. Most distribution networks are radial in nature with limited short-circuit capacity. Therefore, there is a limit to which power can be injected into the distribution network without compromising the power quality and the system stability. This research is aiming to investigate this by applying DG technologies to the grid and keeping the system voltage within a defined boundary [0.95 - 1.05 p.u]. The requirements specified in IEEE Standard 1547 are considered. This research considers four objectives related to minimization of the system power loss, minimization of the deviations of the nodes voltage, minimization of branch current constraint violation, and minimization of feeder’s currents imbalance. The research formulates the problem as a multi-objective problem. The effectiveness of the proposed methods is demonstrated on different revised IEEE test systems including 16 and 33-bus radial distribution system.

Regression testing is just as important for the quality assurance of a system, as it is time consuming. Several techniques exist with the purpose of lowering the execution times of test suites and provide faster feedback to the developers, examples are ones based on transition-models or string-distances. These techniques are called test case selection (TCS) techniques, and focuses on selecting subsets of the test suite deemed relevant for the modifications made to the system under test. This thesis project focused on evaluating the use of a topic model, latent dirichlet allocation, as a means to create a diverse selection of test cases for coverage of certain test characteristics. The model was tested on authentic data sets from two different companies, where the results were compared against prior work where TCS was performed using similarity-based techniques. Also, the model was tuned and evaluated, using an algorithm based on differential evolution, to increase the model’s stability in terms of inferred topics and topic diversity. The results indicate that the use of the model for test case selection purposes was not as efficient as the other similarity-based selection techniques studied in work prior to thist hesis. In fact, the results show that the selection generated using the model performs similar, in terms of coverage, to a randomly selected subset of the test suite. Tuning of the model does not improve these results, in fact the tuned model performs worse than the other methods in most cases. However, the tuning process results in the model being more stable in terms of inferred latent topics and topic diversity. The performance of the model is believed to be strongly dependent on the characteristics of the underlying data used to train the model, putting emphasis on word frequencies and the overall sizes of the training documents, and implying that this would affect the words’ relevance scoring to the better.

The problem addressed in this research is the in-flight generation of trajectories for autonomous unmanned aircraft, which requires a method of generating pseudo-optimal trajectories in near-real-time, on-board the aircraft, and without external intervention. The focus of this research is the enhancement of a particular inverse dynamics direct method that is a candidate solution to the problem. This research introduces the following contributions to the method. A quaternion-based inverse dynamics model is introduced that represents all orientations without singularities, permits smooth interpolation of orientations, and generates more accurate controls than the previous Euler-angle model. Algorithmic modifications are introduced that: overcome singularities arising from parameterization and discretization; combine analytic and finite difference expressions to improve the accuracy of controls and constraints; remove roll ill-conditioning when the normal load factor is near zero, and extend the method to handle negative-g orientations. It is also shown in this research that quadratic interpolation improves the accuracy and speed of constraint evaluation. The method is known to lead to a multimodal constrained nonlinear optimization problem. The performance of the method with four nonlinear programming algorithms was investigated: a differential evolution algorithm was found to be capable of over 99% successful convergence, to generate solutions with better optimality than the quasi- Newton and derivative-free algorithms against which it was tested, but to be up to an order of magnitude slower than those algorithms. The effects of the degree and form of polynomial airspeed parameterization on optimization performance were investigated, and results were obtained that quantify the achievable optimality as a function of the parameterization degree. Overall, it was found that the method is a potentially viable method of on-board near- real-time trajectory generation for unmanned aircraft but for this potential to be realized in practice further improvements in computational speed are desirable. Candidate optimization strategies are identified for future research.

Orientador: José Roberto Sanches Mantovani / Resumo: O problema de alocação ótima de banco de capacitores em sistema de distribuição radiais consiste em definir as barras onde devem ser alocados os bancos de capacitores, além de determinar os tipos, potência nominal e em quais fases eles devem ser alocados, atendendo a restrições físicas e operacionais das redes elétricas, juntamente com os padrões da qualidade de fornecimento normatizados pelas agências reguladoras do setor. Também deve-se definir o esquema de controle, ou seja, quando os bancos capacitivos variáveis devem operar em diferentes níveis de carregamentos. A alocação de bancos de capacitores em sistemas de distribuição é um problema de programação não-linear inteiro misto, não convexo, de difícil solução através de técnicas clássicas de otimização, pela sua natureza combinatória, devido o aumento no número de variáveis inteiras envolvidas na solução de problemas de médio e grande porte. Neste trabalho, propõe-se para a sua solução a meta-heurística de Evolução Diferencial (ED), que deve fornecer a localização e dimensionamento dos bancos de capacitores fixos e chaveados ao longo dos alimentadores primários, em sistemas de distribuição radiais trifásicos e desbalanceados. A alocação deve atender aos critérios de mínimo custo de investimento e operação do sistema, dados pela soma do custo de aquisição, instalação e manutenção dos bancos de capacitores, mais o custo de perdas ativas no sistema além de melhorar o fator de potência. São apresentados neste trabalho, resu... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The optimal allocation problem of capacitor bank in radial distribution systems is to define the bus where the capacitor banks must be allocated, furthermore determine the types, nominal power and which phase they must be allocated as they attended the physical and the operational constraints of power systems in conjunction with the supplier quality standards normalized by the sector regulatory agencies. Moreover, you must define the check schema, in the words, when the variable capacitor banks must operate at different load levels. The allocation of capacitor banks in distribution systems it's a not convex mixed integer nonlinear programming problem with a difficult solution through classical optimization techniques due to the increase of integer variables involved in the solution of large and medium-size problems. This works proposes for the solution, a metaheuristic based on Differential Evolution (DE) which provide the location and the sizing of fixed capacitor banks, switched over the primary feeders in unbalanced three-phase radial distribution systems, with the aim of minimizing the total investment and the system operation cost, given by sum of acquisition cost, installation and maintenance of capacitor banks, plus the cost of active losses in the system and to im-prove the power factor. Results for a 135-bus unbalanced three-phase system are presented. / Mestre

Orientador: Marcelo Carvalho Minhoto Teixeira / Resumo: Este trabalho examina o problema de controle robusto aplicado a sistemas lineares chaveadoscontínuos no tempo através de uma estratégia de chaveamento dependente apenas da saída medida da planta. Em implementações de sistemas de controle com alocação de polos, o vetorde estado pode não estar completamente disponível. Deste modo, é importante desenvolver estratégias de chaveamento que dependam da saída medida da planta. Inicialmente são propostasnovas condições de estabilidade para sistemas lineares chaveados com incertezas politópicasatravés de uma estratégia de chaveamento adequada. Posteriormente considera-se também ochaveamento de realimentações estáticas da saída. Além disto, considera-se a inserção de umcritério de desempenho, neste caso, um custo garantido para sistemas chaveados. Variáveisde folga são acrescentadas nas condições de teoremas dispostos na literatura visando reduziro conservadorismo das desigualdades matriciais lineares. Em sequência, definindo um sistemaaumentado interpretando-se a saída medida da planta como uma nova variável de estado dosistema, são propostas condições originais para a estabilidade que podem reduzir o conservadorismo de técnicas conhecidas. No que tange à realimentação dinâmica de saída, condiçõesde estabilidade e desempenho foram propostas considerando filtros dinâmicos alocados em sériecom a saída medida da planta. Em seguida, apresentam-se condições para o projeto de controladores robustos estáticos/dinâmicos... (Resumo completo, clicar acesso eletrônico abaixo) / Doutor

Fundação de Amparo a Pesquisa do Estado de Minas Gerais / In the last few decades, the application of optimization in engineering problems has grown considerably. There are various optimization methods and the performance of each one depends on the type of problem considered. The natural methods, which are based on probabilistic rules, have been widely studied. The purpose of this work is to present a detailed study of the natural optimization method called Differential Evolution and its strategies. A theoretical formulation is presented. In this work, a revision of Genetic Algorithms and Simulated Annealing is made. These techniques are employed to compare their results to those obtained with Differential Evolution. Classic mathematical functions and some problems of engineering are used in order to verify the efficiency of the studied technique. The Differential Evolution is applied with effectiveness in multi-objective optimization problems with and without the presence of constraints including two complex robotic problems. / Nas últimas décadas, a aplicação de otimização em problemas de engenharia tem crescido consideravelmente. Existem muitos métodos de otimização e o desempenho de cada um deles depende do tipo de problema considerado. Os métodos naturais, que se baseiam em regras probabilísticas, têm sido amplamente estudados. O objetivo deste trabalho é apresentar um estudo detalhado do método de otimização natural denominado Evolução Diferencial e suas estratégias, apresentando sua fundamentação teórica. Neste trabalho é realizada uma revisão de Algoritmos Genéticos e Recozimento Simulado. Estas técnicas são utilizadas para comparar os resultados por elas obtidos com os calculados aplicando Evolução Diferencial. Para verificar a eficiência do método estudado, são utilizados funções matemáticas clássicas e alguns problemas de engenharia. A Evolução Diferencial é aplicada com eficiência em problemas de otimização multi-objetivo, na presença ou não de restrições, incluindo dois problemas complexos em robótica. / Mestre em Engenharia Mecânica