Neste trabalho apresentamos uma nova classe de robos bipedes com pernas articuladas e um corpo central. O projeto de robo proposto faz uso de contrapesos em cada um de seus links, e apresenta propriedades que simplificam excepcionalmente as equações dinâmicas que regem seu movimento. Prova- mos que o sistema encontrado, sob certas hipóteses, é linearizavel por meio de uma realimentaçao não-linear de seus estados. Resolvemos o problema de otimização do tempo de percurso de uma trajetória predefinida para este robo, admitindo-se limitações em seus atuadores. Projetamos um sistema de controle inspirado no conceito de \"flatness\" a fim de rastrear esta política ótima de percurso da trajetória. Testamos a robustez deste sistema em simulações de alguns exemplos numéricos. / In this thesis we present a new class of biped robots with articulate legs and a torso. The proposed design is constructed by means of applying counter- balances to each link of the leg, and therefore it has some properties that simplifies dramatically the dynamics of the robot. We prove that the result- ing system, under certain assumptions, is exact linearizable by a nonlinear feedback. We describe the solution to the time-optimal tracking problem of a predefined trajectory for this robot, assuming that its actuators have torque limits. We designed a control system inspired on the concept of °flatness\"in order to track this reference optimal trajectory. We evaluated the robustness of such system during the simulations of some numerical examples.

There is an emerging need to develop new techniques for control system design that better address the challenges posed by modern large-scale cyber-physical systems. These systems are often massive networks of interconnected and interoperating subsystems that fuse physical processes, embedded computation, automation technologies, and communication. The resulting problems are dimensionally large, exhibit significant time-varying structural variations during operation, and feature complex dynamics, constraints and objectives across local and global-system scales. These properties are difficult to address using traditional control theoretic methods without substantial loss of performance and robustness. To overcome these limitations, this dissertation presents new concepts and methods for control of modern large-scale variably-structured systems through self-assembling and self-configuring control constructs that allow for fundamental restructuring of the control system’s topology in response to the current system structure. We present the System Component Graph (SCG) formulation as a mathematical framework that generalizes and extends directed graph methods from decentralized control. We present algorithms, methods, and metrics for real-time decentralization and control-structure optimization, utilizing the inclusion principle for addressing interconnected overlapping dynamics and optimal linear-quadratic (LQ) methods for local decentralized subsystem control. Global system control and performance is achieved through a centralized planner that provides continuous real-time optimized trajectories as guidance command inputs to each subsystem. We present the method of Random Subcomplement Trees (RST) for pseudo-optimal real-time trajectory planning of large-scale systems which formalizes and extends the method of rapidly-exploring random trees in a control optimization framework. The RST method defines transformations from the higher-dimension state space into an intermediate lower-dimensional search space, where optimal transitions between subspace states are defined. In the context of this approach, the resulting decentralized topology found within the SCG framework provides the RST subspace definition and requisite transformations, and optimal transitions in the search space are found through forward evaluation of the closed-loop decentralized subsystem dynamics. The methods developed in this thesis are applied to a set of real-world problems spanning various domains and demonstrate the application of these methods from first-principle modeling through control system analysis, design, implementation, and evaluation in experimental tests and simulation.

Este trabalho estuda o sistema de controle de um robô móvel, termo que designa veículos sem motorista humano e com capacidade de trafegar por rotas livremente escolhidas. As arquiteturas de controle utilizadas em robôs móveis são analisadas. A arquitetura adotada neste trabalho, de caráter funcional,é apresentada e discutida. O trabalho se concentra nos níveis mais simples de controle, relacionados ao controle de trajetória, cujo objetivo é garantir que o robô móvel percorra uma rota pré-definida. Um controlador de trajetória é proposto e projetado. O controlador resulta da aplicação da teoria de controle ótimo a um modelo de robô móvel em referencial fixo. Uma técnica recente de controle de robôs (técnica de atgs) é empregada para melhorar a robustez do controlador. O desempenho do controlador obtido com uso de atgs é comparado com o desempenho do controlador obtido inicialmente. Com o objetivo de validar esta proposta de controlador de trajetória, resultados fornecidos por simulações são discutidos. A análise do controlador foi respaldada com dados experimentais obtidos junto a um robô móvel, denominado Ariel, desenvolvido no laboratório de automação e sistemas (mecatrônica) da Escola Politécnica da Universidade de São Paulo. / This work studies the Control System of a Mobile Robot, term which refers to vehicles without human driver and with ability to follow arbitrary routes. This work analyses the Control Architectures frequently employed in Mobile Robots. The Architecture here adopted is a functional one, which is presented and described. This work focuses on the simplest levels of Control, those which are mainly related to the Trajectory Control, and whose objective is to guarantee that the Mobile Robot follows a specified route. A Trajectory Controller is proposed and designed. The Controller is based on Optimal Control Theory. A recently developed technique for robot control (called ATGS techinique) is used in order to improve the Controller robustness. Simulation results are discussed in order to validate the proposed Controller. The Controller analysis is tested in a real Mobile Robot (named Ariel) currently developed at Laboratório de Automação e Sistemas (Mecatrônica) , at Escola Politécnica of Universidade de São Paulo.

Este trabalho apresenta aspectos teóricos e práticos relevantes do desenvolvimento do Sistema de Navegação e Controle (SNC) a ser implementado em um Veículo Submarino Semi-Autônomo (VSSA), tipo não carenado e auto propelido, que está em desenvolvimento e construção na Escola Politécnica da USP, para a Petrobrás. Os três graus de liberdade horizontais são controlados para seguirem trajetórias pré-definidas, enviadas como sinais de referência para navegação por uma estação de apoio localizada na superfície, responsável pela guiagem do veículo. Os sinais de referência enviados são acústicos propagados pela água. A implementação física do SNC e o controle dos três graus de liberdade verticais não fazem parte do escopo deste trabalho. O SNC consiste em um controlador determinístico, um seguidor de trajetórias linear quadrático alimentado por um vetor de estados estimado assintoticamente. Por segurança, em caso de falha de algum sensor, e para filtrar ruídos nos sinais medidos, um estimador de estados de ordem plena é utilizado conjuntamente. Pela simplicidade de síntese e implementação, esta arquitetura de controle é considerada a melhor alternativa para capacitar o VSSA a executar os movimentos semi-autônomos desejados. As técnicas de controle utilizadas requerem a linearização do modelo matemático não-linear que descreve o comportamento dinâmico do veículo. O modelo é obtido de maneira simplificada. Os resultados são gerados por simulações com o modelo não-linear. / This work presents theoretical and practical aspects of the development of the Navigation and Control System (NCS) to be implemented into a Petrobras\' Semi-Autonomous Underwater Vehicle (SAUV), an open-frame and self-propelled type, which is being developed and built at Escola Politécnica of the University of São Paulo (EPUSP). The three horizontal Degrees-of-Freedom (DoF) are controlled so that they can follow a pre-defined trajectory sent as navigation reference signals to the NCS by a support ship, responsible for the guidance of the vehicle and placed on the ocean surface. Reference signals are sent as acoustic signals through the ocean water. The implementation and the control of the three vertical DoF are not in the scope of the present work. The NCS is based upon a deterministic controller, a Linear Quadratic (LQ) trajectory follower fed by an asymptotically estimated state vector, even though all the state variables are available by direct measurents. For safety, if some sensor fails, and for filtering noise on measured signals, a full-order state estimator is also designed. Since the LQ controller architecture is rather simple to design and implement, it was elected to control the SAUV manoeuvers. The control techniques require a linear model of the dynamics of the vehicle. Hence, a linearization procedure is applied to the system of nonlinear differential equations that describe the dynamic behavior of the SAUV. The results presented are provided by computer-aided simulations with the nonlinear model of the plant.

The theory of the Environmental Kuznets Curve (EKC) proposes to answer important questions regarding the connections between economic growth (development) and the environment. The theory postulates the environment need not always suffer as the economy develops, and it has generated strong support and opposition. Rather than attempting to defend or debunk EKC theory, this research challenges a practice engaged in by proponents and opponents alike. Simplifying assumptions are a necessary part of economic analysis, but this research shows that any assumptions may not be universally applicable. Utilizing, in turn, a simple one good model and then a more complicated two good model, it is discovered that the competing assumptions utilized by proponents and opponents of the EKC theory may both be valid, depending upon the conditions present in the system being analyzed.

Ce travail s’inscrit dans le projet plus global SHARE dont l’objectif principal est de concevoir une station de contrôle sol universelle mono-opérateur de nouvelle génération pour le contrôle et la commande de drones à voilure fixe et voilure tournante.L’objectif de cette thèse est de développer un simulateur générique de la station de contrôle capable de simuler en temps réels les différents types de drones, les capteurs embarqués (caméra), l’environnement et les différentes missions militaires définies par le standard STANAG 4586. Après une modélisation des différentes parties de la station, nous présentons l’architecture adoptée pour le simulateur et le module de contrôle. Ce dernier est divisé en plusieurs niveaux hiérarchiques, dont le niveau supérieur contient les algorithmes de planification de trajectoire pour les drones à voilure fixe HALE (haute altitude, longue endurance). Ces algorithmes servent à calculer un chemin admissible entre un point de départ et un point d’arrivée en minimisant une fonction de coût.Enfin nous avons développé un système d’aide à la décision pour la gestion en ligne des missions, capable de réaliser une sélection d’objectifs, et une sélection du meilleur chemin proposé par les algorithmes de planification de trajectoire. Cet outil a pour objectif d’aider l’opérateur de la station à prendre la meilleure décision en maximisant les récompenses obtenues lors de la réalisation des objectifs et en minimisant certains critères tels que la consommation des ressources, le danger, les conditions météorologiques, etc. / The presented work is part of a larger project called SHARE, which consists in developing a universal new generation ground control station for the monitoring and the control of fixed and rotary wing UAVs (Unmanned Aerial Vehicle).The objective of this PhD thesis is to develop a generic ground control station simulator capable of simulating in real time different types of UAVs, onboard sensors, several flight environments, and various military missions which are defined according to the STANAG 4586 standard. First, we introduce the model of the different parts of the station, and then we present the architecture adopted for the simulator and the control module. The latter is divided into several hierarchical levels; the upper level contains the path planning algorithms for fixed wing HALE (High Altitude, Long Endurance) UAV. These algorithms are used to calculate an admissible path between initial and final position by minimizing a cost function.Finally, in order to manage missions online, we developed a decision support system that is capable of performing a variety of objectives. This system also supplies the operator the best paths proposed by planning algorithms. This tool aims to help the station operator to make the decision by maximizing the rewards obtained during the achieving the objectives and minimizing certain criteria (resource consumption, danger, weather,..).

Research Doctorate - Doctor of Philosophy (PhD) / This thesis studies control systems with communication constraints. Such constraints arise due to the fact that practical control systems often use non-transparent communication links, i.e., links subject to data-rate constraints, random data-dropouts or random delays. Traditional control theory cannot deal with such constraints and the need for new tools and insights arises. We study two problems: control with average data-rate constraints and control over analog erasure channels with i.i.d. dropout profiles. When focusing on average data-rate constraints, it is natural to ask whether information theoretic ideas may assist the study of networked control systems. In this thesis we show that it is possible to use fundamental information theoretic concepts to arrive at a framework that allows one to tackle performance related control problems. In doing so, we show that there exists an exact link between control systems subject to average data-rate limits, and control systems which are closed over additive i.i.d. noise channels subject to a signal-to-noise ratio constraint. On the other hand, in the case of control systems subject to i.i.d. data-dropouts, we show that there exists a second-order moments equivalence between a linear feedback system which is interconnected over an analog erasure channel, and the same system when it is interconnected over an additive i.i.d. noise channel subject to a signal-to-noise ratio constraint. From the results foreshadowed above, it follows that the study of control systems closed over signal-to-noise ratio constrained additive i.i.d. noise channels is a task of relevance to many networked control problems. Moreover, the interplay between signal-to-noise ratio constraints and control objectives is an interesting issue in its own right. This thesis starts with such a study. Then, we use the resultant insights to address performance issues in control systems subject to either average data-rate constraints or i.i.d. data-dropouts. Our approach shows that, once key equivalences are exposed, standard control intuition and synthesis machinery can be used to tackle networked control problems in an exact manner. It also sheds light into fundamental results in the literature and gives (partial) answers to several previously open questions. We believe that the insights in this thesis are of fundamental importance and, to the best of the author's knowledge, novel.

Decisions on capacity are often treated separately from those of production and inventory. In most situations, capacity issues are longer-term, so capacity-related decisions are considered strategic and thus not part of supply planning. This research focuses on optimal supply planning with emphasis on variable capacity to meet uncertain demand. It also defines three levels of capacity change: operating hours, labor availability and production hardware availability. The work presented here deals with the fundamental decisions to determine capacity, production, and inventory to meet customer demand while optimizing revenue and costs over a planning horizon (typically the life of the product). With the Lagrangian technique for constrained optimization, it can be shown that the optimal supply capacity has upper and lower bounds. The optimal feedback policy prescribes increasing the supply capacity when at the beginning of the planning interval it is below the lower bound. Similarly, the supply capacity should be decreased to the upper bound when it is above the upper bound. This paper will present arguments for characterizing forecast evolution and information sharing in the supply chain to obtain a predictor-corrector approach to supply chain control. / Singapore-MIT Alliance (SMA)

The solution of optimal control problems through the Hamilton-Jacobi-Bellman (HJB) equation offers guaranteed satisfaction of both the necessary and sufficient conditions for optimality. However, finding an exact solution to the HJB equation is a near impossible task for many optimal control problems. This thesis presents an approximation method for solving finite-horizon optimal control problems involving nonlinear dynamical systems. The method uses finite-order approximations of the partial derivatives of the cost-to-go function, and successive higher-order differentiations of the HJB equation. Natural byproducts of the proposed method provide sensitivities of the controls to changes in the initial states, which can be used to approximate the solution to neighboring optimal control problems. For highly nonlinear problems, the method is modified to calculate control sensitivities about a nominal trajectory. In this framework, the method is shown to provide accurate control sensitivities at much lower orders of approximation. Several numerical examples are presented to illustrate both applications of the approximation method.

Despite the immense progress made by molecular biology in cataloging andcharacterizing molecular elements of life and the success in genome sequencing, therehave not been comparable advances in the functional study of complex phenotypes.This is because isolated study of one molecule, or one gene, at a time is not enough byitself to characterize the complex interactions in organism and to explain the functionsthat arise out of these interactions. Mathematical modeling of biological systems isone way to meet the challenge.My research formulates the modeling of gene regulation as a control problem andapplies systems and control theory to the identification, analysis, and optimal controlof genetic regulatory networks. The major contribution of my work includes biologicallyconstrained estimation, dynamical analysis, and optimal control of genetic networks.In addition, parameter estimation of nonlinear models of biological networksis also studied, as a parameter estimation problem of a general nonlinear dynamicalsystem. Results demonstrate the superior predictive power of biologically constrainedstate-space models, and that genetic networks can have differential dynamic propertieswhen subjected to different environmental perturbations. Application of optimalcontrol demonstrates feasibility of regulating gene expression levels. In the difficultproblem of parameter estimation, generalized EM algorithm is deployed, and a set of explicit formula based on extended Kalman filter is derived. Application of themethod to synthetic and real world data shows promising results.