Esta dissertação trata do problema de processamento de Erros Grosseiros (EGs) com base na aplicação do chamado Índice de Não-Detecção de Erros, ou apenas UI (Undetectability Index), na análise dos resíduos do estimador de estado por mínimos quadrados ponderados. O índice UI foi desenvolvido recentemente e possibilita a classificação das medidas de acordo com as suas características de não refletirem grande parcela de seus erros nos resíduos daquele estimador. As medidas com maiores UIs são aquelas cujos erros são mais difíceis de serem detectados através de métodos que fazem uso da análise dos resíduos, pois grande parcela do erro dessas medidas não aparece no resíduo. Inicialmente demonstrou-se, nesta dissertação, que erros das estimativas das variáveis de estado em um sistema com EG não-detectável (em uma medida de alto índice UI) podem ser mais significativos que em medidas com EGs detectáveis (em medidas com índices UIs baixos). Justificando, dessa forma, a importância de estudos para tornar possível o processamento de EGs em medidas com alto índice UI. Realizou-se, então, nesta dissertação, diversas simulações computacionais buscando analisar a influência de diferentes ponderações de medidas no UI e também nos erros das estimativas das variáveis de estado. Encontrou-se, então, uma maneira que destacou-se como a mais adequada para ponderação das medidas. Por fim, ampliaram-se, nesta dissertação, as pesquisas referentes ao UI para um estimador de estado por mínimos quadrados ponderados híbrido. / This dissertation deals with the problem of Gross Errors processing based on the use of the so-called Undetectability Index, or just UI. This index was developed recently and it is capable to classify the measurements according to their characteristics of not reflecting their errors into the residuals of the weighted least squares state estimation process. Gross errors in measurements with higher UIs are very difficult to be detected by methods based on the residual analysis, as the errors in those measurements are masked, i.e., they are not reflected in the residuals. Initially, this dissertation demonstrates that a non-detectable gross error (error in a measurement with high UI) may affect more the accuracy of the estimated state variables than a detectable gross error (error in a measurement with low UI). Therefore, justifying the importance of studies that make possible gross errors processing in measurements with high UI. In this dissertation, several computational simulations are carried out to analyze the influence of different weights of measurements in the UI index and also in the accuracy of the estimated state variables. It is chosen a way that stood out as the most appropriate for weighing the measurements. Finally, in this dissertation, the studies referring to the UI is extended for a hybrid weighted least squares state estimator.

Most micro air vehicles rely heavily on reliable GPS measurements for proper estimation and control, and therefore struggle in GPS-degraded environments. When GPS is not available, the global position and heading of the vehicle is unobservable. This dissertation establishes the theoretical and practical advantages of a relative navigation framework for MAV navigation in GPS-degraded environments. This dissertation explores how the consistency, accuracy, and stability of current navigation approaches degrade during prolonged GPS dropout and in the presence of heading uncertainty. Relative navigation (RN) is presented as an alternative approach that maintains observability by working with respect to a local coordinate frame. RN is compared with several current estimation approaches in a simulation environment and in hardware experiments. While still subject to global drift, RN is shown to produce consistent state estimates and stable control. Estimating relative states requires unique modifications to current estimation approaches. This dissertation further provides a tutorial exposition of the relative multiplicative extended Kalman filter, presenting how to properly ensure observable state estimation while maintaining consistency. The filter is derived using both inertial and body-fixed state definitions and dynamics. Finally, this dissertation presents a series of prolonged flight tests, demonstrating the effectiveness of the relative navigation approach for autonomous GPS-degraded MAV navigation in varied, unknown environments. The system is shown to utilize a variety of vision sensors, work indoors and outdoors, run in real-time with onboard processing, and not require special tuning for particular sensors or environments. Despite leveraging off-the-shelf sensors and algorithms, the flight tests demonstrate stable front-end performance with low drift. The flight tests also demonstrate the onboard generation of a globally consistent, metric, and localized map by identifying and incorporating loop-closure constraints and intermittent GPS measurements. With this map, mission objectives are shown to be autonomously completed.

Development of dynamic state estimation techniques and their applications in problems of identification in structural engineering have been taken up. The thrust of the study has been the identification of structural systems that exhibit nonlinear behavior, mainly in the form of constitutive and geometric nonlinearities. Methods encompassing both linearization based strategies and those involving nonlinear filtering have been explored. The applications of derivative-free locally transversal linearization (LTL) and multi-step transversal linearization (MTrL) schemes for developing newer forms of the extended Kalman filter (EKF) algorithm have been explored. Apart from the inherent advantages of these methods in avoiding gradient calculations, the study also demonstrates their superior numerical accuracy and considerably less sensitivity to the choice of step sizes. The range of numerical illustrations covers SDOF as well as MDOF oscillators with time-invariant parameters and those with discontinuous temporal variations. A new form of the sequential importance sampling (SIS) filter is developed which explores the scope of the existing SIS filters to cover nonlinear measurement equations and more general forms of noise involving multiplicative and (or) Gaussian/ non-Gaussian noises. The formulation of this method involves Ito-Taylor’s expansions of the nonlinear functions in the measurement equation and the development of the ideal ispdf while accounting for the non-Gaussian terms appearing in the governing equation. Numerical illustrations on parameter identification of a few nonlinear oscillators and a geometrically nonlinear Euler–Bernoulli beam reveal a remarkably improved performance of the proposed methods over one of the best known algorithms, i.e. the unscented particle filter. The study demonstrates the applicability of diverse range of mathematical tools including Magnus’ functional expansions, theory of SDE-s, Ito-Taylor’s expansions and simulation and characterization of the non-Gaussian random variables to the problem of nonlinear structural system identification.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-05-16T17:51:25Z No. of bitstreams: 1 guilhermedeoliveiraalves.pdf: 1293169 bytes, checksum: a76074780b2af177b66be7c6435b16d1 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-06-28T12:25:31Z (GMT) No. of bitstreams: 1 guilhermedeoliveiraalves.pdf: 1293169 bytes, checksum: a76074780b2af177b66be7c6435b16d1 (MD5) / Made available in DSpace on 2016-06-28T12:25:31Z (GMT). No. of bitstreams: 1 guilhermedeoliveiraalves.pdf: 1293169 bytes, checksum: a76074780b2af177b66be7c6435b16d1 (MD5) Previous issue date: 2015-09-18 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O presente trabalho tem por objetivo apresentar uma nova metodologia para estimação estática de estados em sistemas de distribuição de energia elétrica que estima as correntes nos ramos como variáveis de estado utilizando medições de tensão e corrente de ramo fasoriais oriundas de unidades de medição fasorial (Phasor Measurement Units - PMUs). A metodologia consiste em resolver um problema de otimização não linear minimizando uma função objetivo quadrática associada com as medições e estados estimados sujeito às restrições de carga das barras da rede que não apresentam PMUs instaladas baseadas em dados históricos, sendo esta a principal contribuição deste trabalho. Uma proposta de alocação de PMUs também é apresentada e que consiste em alocar duas unidades em cada ramificação do sistema, uma no começo e outra no final do trecho, procurando utilizar o menor número possível e que não comprometa a qualidade dos estados estimados. A resolução do problema de otimização é realizada de duas formas, através da ‘toolbox fmincon’ do software Matlab, que é uma ferramenta muito utilizada na resolução de problemas de otimização, e através da implementação computacional do Método de Pontos Interiores com Barreira de Segurança (Safety Barrier Interior Point Method - SFTB - IPM) proposto na literatura utilizada. Durante o processo de estimação de estados são utilizadas medidas obtidas através de um fluxo de potência que simulam as PMUs instaladas nos sistemas analisados variando o carregamento de cada sistema em torno da sua média histórica de carga até atingir os limites superior e inferior estabelecidos, sendo verificado o comportamento do estimador de estados perante a ocorrência de ruídos brancos nas medidas de todos os sistemas analisados. Foram analisados um sistema de distribuição tutorial de 15 barras e três sistemas encontrados na literatura contendo 33, 50 e 70 barras respectivamente. No sistema tutorial e no de 70 barras foram incluídas unidades de geração distribuída para se verificar o comportamento do estimador de estados. Todos os resultados do processo de estimação de estados são obtidos com os dois métodos de resolução apresentados e são comparados o desempenho de cada método, principalmente em relação ao tempo computacional. Todos os resultados obtidos foram validados usando um programa de fluxo de potência convencional e apresentam boa precisão com valor de função objetivo baixo mesmo na presença de ruídos nas medidas refletindo de maneira confiável o real estado do sistema de distribuição, o que torna a metodologia proposta atraente. / This work aims at presenting a new methodology for static state estimation in electric power distribution systems which estimates the branch currents as state variables using voltage measurements and current phasor branch obtained from phasor measurement units (Phasor Measurement Units - PMUs). The methodology consists of solving a nonlinear optimization problem minimizing a quadratic objective function associated with the estimated measurements and states, subject to load constraints for the non monitored loads based on historical data, which is the main contribution of this work. A PMU allocation strategy is presented which consists of allocating two PMUs for each system branch, one at the beginning and another at the end, trying to use as little PMUs as possible in such a way that the quality of the estimated states are not compromised. The solution of the optimization problem is obtained through two ways, the first is the toolbox ‘fmincon’ from Matlab solver software which is a widely used tool in the optimization problem. The second is a computer implementation of interior point method with security barrier (SFTB - IPM) proposed in the literature. Comparisons of computing times and results obtained with both methods are shown. A power flow program is used to obtain the voltages and branch currents in order to emulate the PMUs data in the state estimation process. Additionaly the non monitored loads are varied from the minimum bounds to their maximum, allowing white noise errors from the PMUs measurements. A tutorial test system of 15 buses is fully explored and three IEEE test systems of 33, 50 and 70 buses are used to show the effectiveness of the proposed methodology. For the tutorial and 70 bus systems, distribued generation units were included to see the state estimator behavior. All results from the state estimation process are obtained considering the two presented solving methods and the computing times performance compared. The results obtained were validated using a conventional power flow program and have good accuracy with low objective function value even in the presence of white noise errors in the measurements reflecting the reliability of the proposed methodology, making it very attractive for distribution system monitoring.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-01-09T11:36:05Z No. of bitstreams: 1 brauliocesardeoliveira.pdf: 2150243 bytes, checksum: 62faa254539b7873aa1393d8cd8f1bf2 (MD5) / Approved for entry into archive by Diamantino Mayra (mayra.diamantino@ufjf.edu.br) on 2017-01-31T11:23:24Z (GMT) No. of bitstreams: 1 brauliocesardeoliveira.pdf: 2150243 bytes, checksum: 62faa254539b7873aa1393d8cd8f1bf2 (MD5) / Made available in DSpace on 2017-01-31T11:23:24Z (GMT). No. of bitstreams: 1 brauliocesardeoliveira.pdf: 2150243 bytes, checksum: 62faa254539b7873aa1393d8cd8f1bf2 (MD5) Previous issue date: 2016-03-08 / O presente trabalho tem por objetivo apresentar uma metodologia para estimação de estados em sistemas de distribuição de energia elétrica. São utilizadas como variáveis de estado as correntes nos ramos. As medições são obtidas por meio de medições fasoriais sincronizadas(PhasorMeasurementUnits-PMUs),sendoqueostiposdemedidasadvindos desses equipamentos são as tensões nodais e as correntes nos ramos. A abordagem é trifásica, portanto representa as características próprias de um sistema de distribuição. A metodologia consiste em resolver um problema de otimização não linear cuja função objetivo associa o erro quadrático das medidas em relação aos estados estimados sujeito às restrições de carga das barras da rede que não possuem PMUs instaladas baseadas em estimativas de cargas obtidas para o instante “t-1”, partindo-se da premissa que em curtos intervalos de tempo a carga não sofre grandes variações, sendo esta em conjunto com a abordagem trifásica as principais contribuições deste trabalho. Outra contribuição do trabalho é a descentralização, com esta técnica pode-se dividir uma determinada rede em vários subsistemas que podem ser resolvidos de forma separada e independente. Isso torna o processo mais rápido do ponto de vista computacional além de permitir o uso do processamento paralelo, visto que já existe um paralelismo natural entre as tarefas que devem ser resolvidas. Outra vantagem da divisão em subsistemas reside no fato do monitoramento de áreas de interesse. Para utilizar a descentralização foi proposta uma alternativa de alocação de PMUs que consiste em posicionar duas unidades em cada ramificação do sistema, uma no começo e outra no final do trecho, procurando utilizar o menor número possível e que não comprometa a qualidade dos estados estimados. A resolução do problema de otimização é realizada através da implementação computacional do Método de Pontos Interiores com Barreira de Segurança (Safety Barrier Interior Point Method - SFTB - IPM) proposto na literatura especializada. As medidas das PMUs foram obtidas através de um Fluxo de Potência Trifásico via Injeção de Correntes (FPTIC). Foram realizadas diversas simulações variando-se o percentual da carga e os resultados obtidos foram comparados com outra metodologia existente na literatura e com os valores verdadeiros que foram obtidos através do FPTIC para as barras não monitoradas. Foram tambémcomparadosotempocomputacionalentreaexecuçãoserialeaexecuçãoutilizando o processamento paralelo. Os testes mostraram bons resultados o que torna a metodologia proposta aplicável na supervisão de sistemas de distribuição. / This work aims to present a methodology for static state estimation in electric power distribution systems. Branch currents are used as state variables. Measurements are obtained by means of Phasor Measurement Units (PMUs), in which voltage and current branches measurements are used. The approach is three-phase, thus represents the distribution system characteristics. The methodology consists of solving a nonlinear optimization problem minimizing a quadratic objective function associated with the estimated measurements and states subject to load constraints for the non monitored loads based on estimated load obtained from the ‘t-1’ instant, starting from the assumption that in short time intervals the load does not have large variations, which together with the the three-phase approach are the main contributions of this work. Another contribution of this work is the descentralided approach, with this assumption the network can be divided into several subnetworks that can be solved separately and independently. This speeds up the process of being solved from a computational point of view and allows the use of parallel processing, since there is already a natural parallelism among tasks to be solved. Another advantage of the division into subsystems is the fact that the monitoring areas of interest. With the aim of allowing the decentralization was proposed PMUs allocation strategy that consists of allocating two units for each lateral feeder, one at the beginning and one at the end, trying to use as little PMUs as possible in such a way that the quality of the estimated states are not compromised. The resolution of the optimization problem is done through a computer implementation of Interior Point Method with Security Barrier (SFTB - IPM) proposed in the literature. The PMUs measurements were emulated using a Three-PhasePowerFlowusingtheCurrentInjectionmethod(FPTIC).Severalsimulations were performed varying the load percentage and the results obtained were compared with other existing methodology in literature and also the true values that were obtained from the FPTIC to non monitored loads. The computational time using serial and parallel processing were also compared. Results show good results which makes the proposed methodology applicable in monitoring distribution systems.

In large-scale civil structures, a limited number of sensors are placed to monitor the health of civil structures to reduce maintenance, communication and energy costs. In this thesis, the problem of optimal sensor location placement to infer the health of civil structures is explored. First, a comparative study of approaches from the fields of control engineering and civil engineering is conducted . The widely used civil engineering approaches such as effective independence (EI) and modal assurance criterion (MAC) have limitations because of the negligence of modes and damping parameters. On the other hand, control engineering approaches consider the entire system dynamics using impulse response-type sensor measurement data. Such inference can be formulated as an estimation problem, with the dynamics formulated as a second-order differential equation. The comparative study suggests that damping dynamics play significant impact to the selection of best sensor location---the civil engineering approaches that neglect the damping dynamics lead to very different sensor locations from those of the control engineering approaches. In the second part of the thesis, an initial attempt to directly connect the topological graph of the structure (that defines the damping and stiffness matrices) and the second-order dynamics is conducted.

Rýchlosť vozidla je jednou z kľúčových stavových premenných, ktorej znalosť je potrebná v reálnom čase a s vysokou presnosťou, aby mohla slúžiť ako vstupná veličina pre systémy kontroly dynamiky vozidla. Jej priame meranie vo vozidle je však finančne náročné. Riešením tohoto problému môže byť použitie meraní zo senzorov bežne dostupných na palube vozidla a ich následný prepočet na rýchlosť vozidla. Tieto merania sú však veľmi zaťažené procesným šumom, čo vyplýva z komplexnosti pohybu vozidla. Preto je nutné vyvinúť algoritmus so schopnosťou vysporiadať sa s týmito negatívnymi vplyvmi. Algoritmus prezentovaný v tejto práci odhaduje pozdĺžnu rýchlosť vozidla s použitím meraní uhlových rýchlostí štyroch kolies, pozdĺžnej akcelerácie, momentov motora, rýchlosti otáčania okolo zvislej osi a natočenia volantu. Algoritmus bol testovaný na veľkom počte situácií považovaných za kritické na odhad rýchlosti vozidla, ako napríklad prudká akcelerácia na vozovke s nízkym koeficientom trenia, núdzové brzdenie s aktiváciou ABS, či jazda v kopci s kolesami v preklze, prinášajúc uspokojujúce výsledky.

Tato práce je zaměřena na výzkum moderních metod automatického řízení letu a jejich ověření s ohledem na současný stav poznání a budoucí využití bezpilotních letadlových systémů. Práce představuje proces návrhu automatického systému řízení letu s důrazem na přístupy z oblasti návrhu založeného na modelování (Model-Based Design). Nedílnou součástí tohoto procesu je tvorba matematického modelu letounu, který byl využit k syntéze zákonů řízení a k vytvoření simulačního rámce pro evaluaci stability a kvality regulace automatického systému řízení letu. Jádro této práce se věnuje syntéze zákonů řízení založených na unikátní kombinaci teorie optimálního a adaptivního řízení. Zkoumané zákony řízení byly integrovány do digitálního systému řízení letu, jenž umožňuje vysoce přesné automatické létání. Závěrečná část práce se zabývá ověřením a analýzou navrženého systému řízení letu a je rozdělena do 3 fází. První fáze ověření obsahuje evaluaci robustnosti a analyzuje stabilitu a robustnost navrženého systému řízení letu ve frekvenční oblasti. Druhá fáze, evaluace kvality regulace, probíhala v rámci počítačových simulací s využitím vytvořených matematických modelů v časové oblasti.  V poslední fázi ověření došlo k integraci navrženého systému řízení letu do experimentálního letounu, sloužícího jako testovací platforma pro budoucí bezpilotní letadlové systémy a jeho evaluaci v rámci série letových experimentů.

Micro air vehicles have recently gained popularity due to their potential as autonomous systems. Their future impact, however, will depend in part on how well they can navigate in GPS-denied and GPS-degraded environments. In response to this need, this dissertation investigates a potential solution for GPS-denied operations called relative navigation. The method utilizes keyframe-to-keyframe odometry estimates and their covariances in a global back end that represents the global state as a pose graph. The back end is able to effectively represent nonlinear uncertainties and incorporate opportunistic global constraints. The GPS-denied research community has, for the most part, neglected to consider fixed-wing aircraft. This dissertation enables fixed-wing aircraft to utilize relative navigation by accounting for their sensing requirements. The development of an odometry-like, front-end, EKF-based estimator that utilizes only a monocular camera and an inertial measurement unit is presented. The filter uses the measurement model of the multi-state-constraint Kalman filter and regularly performs relative resets in coordination with keyframe declarations. In addition to the front-end development, a method is provided to account for front-end velocity bias in the back-end optimization. Finally a method is presented for enabling multiple vehicles to improve navigational accuracy by cooperatively sharing information. Modifications to the relative navigation architecture are presented that enable decentralized, cooperative operations amidst temporary communication dropouts. The proposed framework also includes the ability to incorporate inter-vehicle measurements and utilizes a new concept called the coordinated reset, which is necessary for optimizing the cooperative odometry and improving localization. Each contribution is demonstrated through simulation and/or hardware flight testing. Simulation and Monte-Carlo testing is used to show the expected quality of the results. Hardware flight-test results show the front-end estimator performance, several back-end optimization examples, and cooperative GPS-denied operations.

Micro aerial vehicles and other autonomous systems have the potential to truly transform life as we know it, however much of the potential of autonomous systems remains unrealized because reliable navigation is still an unsolved problem with significant challenges. This dissertation presents solutions to many aspects of autonomous navigation. First, it presents ROSflight, a software and hardware architure that allows for rapid prototyping and experimentation of autonomy algorithms on MAVs with lightweight, efficient flight control. Next, this dissertation presents improvments to the state-of-the-art in optimal control of quadrotors by utilizing the error-state formulation frequently utilized in state estimation. It is shown that performing optimal control directly over the error-state results in a vastly more computationally efficient system than competing methods while also dealing with the non-vector rotation components of the state in a principled way. In addition, real-time robust flight planning is considered with a method to navigate cluttered, potentially unknown scenarios with real-time obstacle avoidance. Robust state estimation is a critical component to reliable operation, and this dissertation focuses on improving the robustness of visual-inertial state estimation in a filtering framework by extending the state-of-the-art to include better modeling and sensor fusion. Further, this dissertation takes concepts from the visual-inertial estimation community and applies it to tightly-coupled GNSS, visual-inertial state estimation. This method is shown to demonstrate significantly more reliable state estimation than visual-inertial or GNSS-inertial state estimation alone in a hardware experiment through a GNSS-GNSS denied transition flying under a building and back out into open sky. Finally, this dissertation explores a novel method to combine measurements from multiple agents into a coherent map. Traditional approaches to this problem attempt to solve for the position of multiple agents at specific times in their trajectories. This dissertation instead attempts to solve this problem in a relative context, resulting in a much more robust approach that is able to handle much greater intial error than traditional approaches.