O objetivo do trabalho é apresentar dois algoritmos para a solução de problemas de controle ótimo quadrático robusto com restrições, dentro de um contexto de controladores preditivos (MPC do inglês Model Predictive Control). Inicialmente apresentamos uma breve introdução aos algoritmos MPC, com ênfase na abordagem do controlador linear quadrático. Em seguida são apresentados os dois algoritmos de interesse, que utilizam técnicas de otimização LMI. Dessa forma as restrições e as incertezas podem ser colocadas em formas computacionalmente tratáveis. Por fim são realizadas simulações e comparações entre esses algoritmos, bem como com técnicas de MPC encontradas na literatura atual. / The goal of the work is to present two algorithms for the solution of robust quadratic optimal control problems with restrictions, within a model predictive control (MPC) setup. Initially we present a brief introduction of the MPC algorithms, emphasizing the linear quadratic controller approach. Next the two algorithms of interest, using LMI optimization techniques, are presented. By using this technique the restrictions and uncertainties can be written in a computational way. Finally some simulations and comparisons between these algorithms, as well as with MPC techniques found in the current literature, are performed.

Este texto apresenta um método alternativo de regressão que é denominado regressão L1. Este método é robusto com relação a outliers na variável Y enquanto o método tradicional, mínimos quadrados, não oferece robustez a este tipo de outlier. Neste trabalho reanalisaremos os dados sobre imóveis apresentados por Narula e Wellington (1977) à luz da regressão L1. Ilustraremos os principais resultados inferenciais como: interpretação do modelo, construção de intervalos de confiança e testes de hipóteses para os parâmetros, análise de medidas de qualidade do ajuste do modelo e também utilizaremos medidas de diagnóstico para destacar observações influentes. Dentre as medidas de influência utilizaremos a diferença de verossimilhanças e a diferença de verossimilhanças condicional. / This text presents an alternative method of regression that is called L1 regression. This method is robust to outliers in the Y variable while the traditional least squares method does not provide robustness to this type of outlier. In this work we will review the data about houses presented by Narula and Wellington (1977) in the light of the L1 regression. We will illustrate the main inferential results such as: model interpretation, construction of confidence intervals and hypothesis tests for the parameters, analysis of quality measures of model fit and also use diagnostic measures to highlight influential observations. Among the measures of influence we will use the likelihood displacement and the conditional likelihood displacement.

L’objectif de cette thèse était de valider l’ensemble des informations délivrées par les capteurs utiles à la commande d’une station de traitement des eaux usées. Pour cela, nous avons utilisé l’analyse en composantes principales (ACP) pour effectuer la détection et localisation de défauts de capteurs de la station de traitement des eaux usées. Afin de construire un modèle ACP, nous avons eu recours à une matrice de données constituée de l’ensemble des mesures disponibles (obtenues lors du fonctionnement normal de la station de traitement des eaux usées) dans l’installation. Cependant, afin d’appliquer l’ACP, nous avons rencontré plusieurs difficultés : 1. Présence dans les données de valeurs aberrantes (valeurs obtenues durant des périodes de démarrage, d’arrêt, de fonctionnement dégradé, erreurs de mesure, ...) perturbant la construction d’un modèle ACP. 2. Présence de défauts multiples, ce qui entraîne une explosion combinatoire des scénarii de défauts à considérer. Afin de résoudre le premier point, nous nous sommes intéressé aux variantes robustes de l’ACP. L’estimateur robuste MCD (Minimum Covariance Determinant), méthode de référence pour ses performances, nécessite un temps de calcul important, et une connaissance a priori de la quantité de valeurs aberrantes présente dans les données (inconnue). C’est la raison pour laquelle nous avons proposé une nouvelle méthode robuste, basée sur l’utilisation de MM-estimateur, nommée MMRPCA (MM-estimator Robust Principal Component Analysis). Concernant le point 2, une méthode d’analyse du modèle en terme de capacité de détection et de localisation a été appliquée afin de réduire le nombre de défauts à considérer. Les différentes méthodes développées ont été menées avec succès afin de valider les mesures issues des différents capteurs de la station d’épuration des eaux usées / This thesis deals with the validation of the information provided by the sensors to the control of a wastewater treatment plant. For this purpose, Principal Component Analysis (PCA) approach is used in order to accomplish sensor fault detection and isolation of the wastewater treatment plant. This approach is well adapted to cope with diagnosis of complex systems because no a priori theoretical model of the plant must be considered. A data matrix, obtained by taking into consideration the available measurements in normal behaviour of the wastewater treatment plant, is used in order to build a PCA model. However, two major problems must be taking into consideration when PCA is implemented: 1. Outliers appear naturally in the collection data (caused for example by faulty data, data obtained during shutdown or startup periods or data issued from different operating mode) and consequently the PCA model can seriously be affected. 2. Multiple sensor faults introduce unavoidably a combinatory explosion of the different fault scenarios to be considered. The first problem is solved by introducing a robustness degree in the PCA methodology. Among the existing robust methods proposed in the literature, the robust estimator MCD (Minimum Covariance Determinant) is the most popular. However, this method needs a large computing time on the one hand and a priori knowledge of the quantity of outliers present (generally unknown) in the data on the other hand. To avoid these difficulties, a new robust method is proposed in this thesis. Our method, namely MMRPCA (MM-estimator Robust Principal Component Analysis), is based on MM-estimators. The second mentioned problem is tackled by reducing the considered number of faults thanks to a new analysis method of the capacities of detection and isolation of the PCA model. The efficiency of the proposed methodologies is verified by considering the real wastewater treatment plant data

Estimativas robustas de parâmetros populacionais de cetáceos são necessárias para a criação de estratégias de manejo e de conservação eficazes. Dentre os métodos comumente utilizados para estimar parâmetros demográficos, o método de captura e recaptura tem se destacado devido às suas vantagens e precisão. O objetivo deste estudo foi estimar parâmetros populacionais do boto-cinza, Sotalia guianensis, no estuário de Cananéia (25° 03\' S; 47° 55\' W), mediante o uso de modelos de captura-recaptura. O delineamento robusto de Pollock foi utilizado para estimar abundância, sobrevivência, emigração temporária e probabilidades de captura. Levantamentos de fotoidentificação sistemáticos foram conduzidos em três temporadas entre janeiro de 2015 e fevereiro de 2016. O modelo que melhor representou os dados mostrou uma população com sobrevivência constante, emigração temporária aleatória e probabilidades de captura com heterogeneidade variando no tempo e entre as estações. Foram estimados 430 (95% CI: 410-451) indivíduos no verão/2015; 384 (95% CI: 366-403) indivíduos no inverno/2015; e 414 (95% CI: 392-438) indivíduos no verão de 2016. A taxa de emigração temporária (γ\'\'=γ\') foi de 0,05 (± 0,03) e a estimativa de sobrevivência aparente foi de 0,86 (± 0,06). As probabilidades de captura variaram entre as temporadas e os períodos secundários, com valores médios de 0,24 (± 0,02) no verão de 2015; 0,34 (± 0,03) no inverno de 2015; e 0,24 (± 0,03) no verão de 2016. Esses resultados sugerem que as variáveis ambientais entre as estações do ano têm pouco efeito sobre o tamanho da população local, a qual se encontra em equilíbrio e utiliza uma área ainda protegida de ameaças à sua perpetuação. / Reliable estimates of cetacean population parameters are necessary for effective management and conservation strategies. Capture-recapture methods have been commonly used to estimate demographic parameters because of their advantages and accuracy under a set of assumptions. The aim of this study was to estimate population parameters of Guiana dolphins, Sotalia guianensis, in the Cananeia estuary (25°03\' S; 47°55\' W) using capture-recapture models. The Pollock\'s robust design was used to estimate abundance, survival, temporary emigration and capture probabilities. Systematic boat-based photo-identification surveys were conducted in three seasons between Jan/2015 and Feb/2016. The best fitting model showed a population with constant survival, random temporary emigration and heterogeneous time-varying capture probabilities. Population sizes were of 430 (95% CI: 410-451) individuals in summer of 2015, 384 (95% CI: 366-403) individuals in winter of 2015 and 414 (95% CI: 392-438) individuals in summer of 2016. Temporary emigration rate (γ\'\'=γ\') was 0.05 (± 0.03) and apparent survival estimate was 0.86 (± 0.06). Capture probabilities varied greatly among seasons and secondary periods with mean values of 0.24 (± SE 0.02) in summer of 2015, 0.34 (± SE 0.03) in winter of 2015 and 0.24 (± SE 0.03) in summer of 2016. These results suggest that environmental variables between seasons have little effect on the size of the local population, which is stable and uses an area that is still protected from threats.

Nos últimos anos, percebeu-se um avanço substancial das metodologias sistemáticas de seleção de ativos em portfólios financeiros, baseadas em técnicas de otimização. A maior pressão por desempenho sobre as gestoras de recursos e a evolução dos softwares e pacotes de otimização foram fatores que contribuíram para esse desenvolvimento. Dentre as técnicas mais reconhecidas utilizadas na gestão de portfólios está a de otimização robusta, cuja aplicação na solução de problemas com dados incertos iniciou-se na década de 1970 e, desde então, vem evoluindo em sofisticação. Partindo de uma extensão recente do método, propõe-se um novo modelo linear que resolve o problema de otimização de um portfólio para múltiplos estágios, com inovações no tratamento da incerteza das estimativas de dispersão dos retornos. Os resultados mostram que o método proposto desempenha muito bem em termos de rentabilidade e de métricas de risco-retorno em momentos de turbulência dos mercados. Por fim, demonstra-se empiricamente que o modelo alcança um desempenho ainda melhor em termos de rentabilidade com a adoção de um estimador eficiente para o valor esperado dos retornos e com a simultânea redução do nível de robustez do modelo. / It has been realized in the last years a remarkable development of the optimization techniques to solve the problem of financial portfolio selection. The pressure on asset management firms to maintain a more stable performance and the evolution of specialized software packages have enabled this positive trend. One of the most recognized approaches applied to the management of investments is the robust optimization, whose use on uncertain portfolio optimization problems has begun in the 1970s and has experienced a substantial growth since then. Building on a recent version of this framework, it is proposed a new linear model of the robust multistage portfolio optimization problem, thereby incorporating uncertainty about dispersion inputs in an innovative way. The results show that this method performs very well during high volatility periods in terms of the terminal wealth and the risk-return tradeoff. Finally, it can be demonstrated empirically that the proposed method outperforms when an efficient return estimator is incorporated to the optimization model and the robustness level is reduced simultaneously.

Colunas de destilação de alta pureza são sistemas de difícil controle. Apresentam longo tempo de resposta, comportamento altamente não linear e grande interação entre as variáveis. Os controladores preditivos são muito utilizados para o controle de colunas de destilação. Porém, em colunas de alta pureza, a incorporação de um único modelo linear geralmente acarreta em um controle de fraco desempenho. Isto pois, a representação do processo é deficiente, já que não considera variações nos ganhos e nas dinâmicas, típicas de um comportamento não linear. Estas incertezas podem, inclusive, provocar a instabilidade do controle o que resultaria em produtos que não atendam à especificação. Este trabalho tem por objetivo avaliar o desempenho dos controladores de horizonte de predição infinito com um modelo interno e com múltiplos modelos tendo o HYSYS(TM) como simulador de uma coluna de separação benzeno/tolueno e o MATLAB(TM) como ambiente para o controle supervisório. Observa-se que o controlador com apenas um modelo não é capaz de estabilizar o processo para perturbação nos valores de referência das variáveis controladas, ao contrário do controlador com múltiplos modelos. / High-purity distillation columns are systems which are typically difficult to control. The main reason for this is a strongly nonlinear and interactive system associated with a very sluggish response. Model Predictive Control is widely used for control of distillation columns. However, for high-purity columns, the use of a single linear model in the controller usually leads to a poor performance of the control system. The reason for this is the poor system representation, since variation in the system gains and time constants are not taken into account in the computation of the control law. Model uncertainties can produce instability in the control system and consequent deterioration of the product quality. The goal of this work is to evaluate the performance of infinite horizon MPC with a single internal model and with multiple models. HYSYS(TM) is used as simulator for the benzene/toluene column, and MATLAB(TM) is used as a platform for supervisory control. It is observed that the controller with a single model is not capable of stabilizing the process for disturbance in the set point of the controlled variables. Opposite to that behavior the controller with multiple models has a good performance.

Escavadeiras hidráulicas são máquinas versáteis, amplamente utilizadas na construção civil e mineração. Máquinas melhores, mais produtivas, eficientes e que oferecem segurança ao operador são uma demanda constante da indústria. Devido a estes fatores, o controle para a automação de uma escavadeira hidráulica tem sido investigado. Este estudo tem o seu foco voltado para o controle do manipulador do equipamento, que é considerado como um dos elementos fundamentais para o desenvolvimento de uma escavadeira automática. Para desenvolver um sistema de controle viável, primeiramente, foi realizado a modelagem matemática dos subsistemas mecânico e hidráulico do manipulador; posteriormente esses modelos foram acoplados para representar a interação dos subsistemas. Todos os modelos desenvolvidos foram comparados com modelos de referência, obtidos a partir de softwares comerciais dedicados a modelagem de sistema dinâmicos. Tendo sido verificado a capacidade de representação física dos modelos, a fase de projeto do controlador para o manipulador foi iniciada. Para que o controlador seja eficiente, este deve ter duas propriedades essenciais: robustez para lidar com as incertezas e distúrbios severos, e adaptabilidade para lidar com um ambiente de operação altamente dinâmico. A fim de projetar um controlador que considera a dinâmica de cada subsistema do manipulador, a técnica de controle em cascata foi adotada. Esta consiste em dividir o sistema global em subsistemas, de tal forma que seja possível projetar um controlador para cada subsistema. Devido à complexidade do modelo matemático, técnicas avançadas de controle linear e não linear foram combinadas no projeto dos controladores dos subsistemas. O controlador sintetizado foi testado através de simulação numérica, em ambiente MATLAB/Simulink®, na execução de um ciclo completo de trabalho pelo manipulador. Os resultados obtidos foram considerados satisfatórios, mesmo na presença de incertezas, distúrbios severos e de ruídos. Posteriormente, na comparação desses resultados com os de outros controladores, ficou claro que o melhor desempenho foi obtido com o controlador proposto. Isto indica a possível aplicabilidade de tal controlador para a automação deste tipo de equipamento. / Hydraulic excavators are versatile machines, widely used in civil construction and in mining. Better, more productive, and efficient machines that offer operator safety are a constant industry demand. Due to these factors, the control for the automation of a hydraulic excavator has been investigated. This study focuses on the control of the equipment\'s manipulator, which is considered as one of the fundamental elements for the development of an automatic excavator. To develop a viable control system, first, the mathematical modeling of the mechanical and hydraulic subsystems of the manip-ulator was carried out; later these models were coupled to represent the interaction between the subsystems. All the developed models were compared with reference models, obtained from a commercial software dedicated to dynamic system modeling. Having verified the physical representation capacity of the analytical models, the de-sign phase of the controller was started. For the controller to be efficient, it must have two essential properties: robustness to deal with severe uncertainties and disturb-ances, and adaptability to handle a highly dynamic operating environment. To design a controller that considers the dynamics of each subsystem of the manipulator, the cascade control technique was adopted. This consists of dividing the global system into subsystems, in such a way that it is possible to design a controller for each sub-system. Due to the complexity of the mathematical model, advanced linear and non-linear control techniques were combined in subsystem controllers design. The synthe-sized controller was tested by numerical simulation, in MATLAB/Simulink® environ-ment, in the execution of a complete work operation by the manipulator. The results obtained were considered satisfactory, even in the presence of uncertainties, severe disturbances and noise. Subsequently, in the comparison of these results with those of others controllers, it was clear that the best performance was obtained with the pro-posed controller. This indicates the possible applicability of such a controller to the automation of this type of equipment.

Despite the fact that significant progress has been made on the research of these two problems for nonlinear systems for over two decades, many problems are still open. In particular, so far the output regulation problem is mainly handled by robust control approach. This approach has certain fundamental limitations and cannot handle the following three cases. (1) The control direction is unknown. (2) The boundaries of system uncertainties are unknown. (3) The exosystem is not known precisely. / Stabilization and output regulation are two fundamental control problems. The output regulation problem aims to design a feedback controller to achieve asymptotic tracking of a class of reference inputs and rejection of a class of disturbances in an uncertain system while maintaining the internal stability of the closed-loop system. Thus the output regulation problem is more demanding than the stabilization problem. Nevertheless, under some assumptions, the output regulation problem can be converted into a stabilization problem for a well defined augmented system and the solvability of the stabilization problem for this augmented system implies that of the output regulation problem for the original plant. Therefore, to a large extent, the study of the stabilization problem will also lay a foundation for that of the output regulation problem. / To handle these problems and overcome the shortcomings of the robust control approach, in this thesis, we have incorporated the adaptive control approach with the robust control approach. Both stabilization problem and output regulation problem are considered for two important classes of nonlinear systems, namely, the output feedback systems and lower triangular systems. The main contributions are summarized as follows. (1) The adaptive output regulation problem for nonlinear systems in output feedback form is addressed without knowing the control direction. The Nussbaum gain technique is incorporated with the robust control technique to handle the unknown control direction and the nonlinearly parameterized uncertainties in the system. To overcome the dilemma caused by the unknown control direction and the nonlinearly parameterized uncertainties, we have adopted a Lyapunov direct method to solve the adaptive output regulation problem. (2) The adaptive stabilization problem for nonlinear systems in lower triangular form is solved when both static and dynamic uncertainties are present and the control direction is unknown. Technically, the presence of dynamic uncertainty has made the stabilization problem more difficult than the previous work. We have managed to combine the changing supply rate technique and the Nussbaum gain technique to deal with this difficulty. The result is also applied to solve the output regulation problem for lower triangular systems with unknown control direction. (3) The adaptive output regulation problem for nonlinear systems in output feed-back form with unknown exosystem is studied. The adaptive control technique is applied to estimate the unknown parameter results from the unknown exosystem. The condition under which the parameter estimation converges to its real value is also discussed. Further, the global disturbance rejection problem for nonlinear systems in lower triangular form is solved by formulating the unknown external disturbance as a signal produced by an unknown exosystem. (4) The theoretical results have been applied to several typical control systems leading to the solution of some long standing open problems. Some exemplified applications are: (a) Global adaptive stabilization of Chua's circuit without knowing the control direction; (b) Global output synchronization of the Chua's circuit and the harmonic system; (c) Global adaptive disturbance rejection problem of the Duffing's system with all parameters unknown; (d) Global adaptive output regulation of Van der Pol oscillator with an uncertain exosystem. / Liu, Lu. / Adviser: Jie Huang. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3693. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 204-214). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

"A number of outstanding problems in robotic motion and manipulation involve tasks where degrees of freedom (DoF), be they part of the robot, an object being manipulated, or the surrounding environment, cannot be accurately controlled by the actuators of the robot alone. Rather, they are also controlled by physical properties or interactions - contact, robot dynamics, actuator behavior - that are influenced by the actuators of the robot. In particular, we focus on two important areas of poorly controlled robotic manipulation: motion planning for deformable objects and in deformable environments; and manipulation with uncertainty. Many everyday tasks we wish robots to perform, such as cooking and cleaning, require the robot to manipulate deformable objects. The limitations of real robotic actuators and sensors result in uncertainty that we must address to reliably perform fine manipulation. Notably, both areas share a common principle: contact, which is usually prohibited in motion planners, is not only sometimes unavoidable, but often necessary to accurately complete the task at hand. We make four contributions that enable robot manipulation in these poorly controlled tasks: First, an efficient discretized representation of elastic deformable objects and cost function that assess a ``cost of deformation' for a specific configuration of a deformable object that enables deformable object manipulation tasks to be performed without physical simulation. Second, a method using active learning and inverse-optimal control to build these discretized representations from expert demonstrations. Third, a motion planner and policy-based execution approach to manipulation with uncertainty which incorporates contact with the environment and compliance of the robot to generate motion policies which are then adapted during execution to reflect actual robot behavior. Fourth, work towards the development of an efficient path quality metric for paths executed with actuation uncertainty that can be used inside a motion planner or trajectory optimizer."

Identity based cryptography was first proposed by Shamir in 1984. Rather than deriving a public key from private information, which would be the case in traditional public key encryption schemes, in identity based schemes a user's identity plays the role of the public key. This reduces the amount of computations required for authentication, and simplifies key-management. Efficient and strong implementations of identity based schemes are based around easily computable bilinear mappings of two points on an elliptic curve onto a multiplicative subgroup of a field, also called pairing. The idea of utilizing the identity of the user simplifies the public key infrastructure. However, since pairing computations are expensive for both area and timing, the proposed identity based cryptosystem are hard to implement. In order to be able to efficiently utilize the idea of identity based cryptography, there is a strong need for an efficient pairing implementations. Pairing computations could be realized in multiple fields. Since the main building block and the bottleneck of the algorithm is multiplication, we focused our research on building a fast and small arithmetic core that can work on multiple fields. This would allow a single piece of hardware to realize a wide spectrum of cryptographic algorithms, including pairings, with minimal amount of software coding. We present a novel unified core design which is extended to realize Montgomery multiplication in the fields GF(2^n), GF(3^m), and GF(p). Our unified design supports RSA and elliptic curve schemes, as well as identity based encryption which requires a pairing computation on an elliptic curve. The architecture is pipelined and is highly scalable. The unified core utilizes the redundant signed digit representation to reduce the critical path delay. While the carry-save representation used in classical unified architectures is only good for addition and multiplication operations, the redundant signed digit representation also facilitates efficient computation of comparison and subtraction operations besides addition and multiplication. Thus, there is no need for transformation between the redundant and non-redundant representations of field elements, which would be required in classical unified architectures to realize the subtraction and comparison operations. We also quantify the benefits of unified architectures in terms of area and critical path delay. We provide detailed implementation results. The metric shows that the new unified architecture provides an improvement over a hypothetical non-unified architecture of at least 24.88 % while the improvement over a classical unified architecture is at least 32.07 %. Until recently there has been no work covering the security of pairing based cryptographic hardware in the presence of side-channel attacks, despite their apparent suitability for identity-aware personal security devices, such as smart cards. We present a novel non-linear error coding framework which incorporates strong adversarial fault detection capabilities into identity based encryption schemes built using Tate pairing computations. The presented algorithms provide quantifiable resilience in a well defined strong attacker model. Given the emergence of fault attacks as a serious threat to pairing based cryptography, the proposed technique solves a key problem when incorporated into software and hardware implementations. In this dissertation, we also present an efficient accelerator for computing the Tate Pairing in characteristic 3, based on the Modified Duursma Lee algorithm.