Esta tese examina o problema de detecção de conectividade entre séries temporais no sentido de Granger no caso em que a natureza não linear das interações não permite sua determinação por meio de modelos auto-regressivos lineares vetoriais. Mostra-se que é possível realizar esta detecção com auxílio dos chamados métodos de Kernel, que se tornaram populares em aprendizado por máquina (\'machine learning\') já que tais métodos permitem definir formas generalizadas de teste de Granger, coerência parcial direcionada e função de transferência direcionada. Usando simulações, mostram-se alguns exemplos de detecção nos quais fica também evidente que resultados assintóticos deduzidos originalmente para estimadores lineares podem ser generalizados de modo análogo, mostrando-se válidos no presente contexto kernelizado. / This work examines the connectivity detection problem between time series in the Granger sense when the nonlinear nature of interactions determination is impossible via linear vector autoregressive models, but is, nonetheless, feasible with the aid of the so-called Kernel methods that are popular in machine learning. The kernelization approach allows defining generalised versions for Granger tests, partial directed coherence and directed transfer function, which the simulation of some examples shows that the asymptotic detection results originally deducted for linear estimators, can also be employed under kernelization if suitably adapted.

O presente trabalho avaliou o uso do lodo residual (biossólido) produzido nas Estações de Tratamento de Esgoto (ETEs) da Região Metropolitana de São Paulo (RMSP) como fertilizante em florestas de eucaliptos. Os aspectos estudados foram demanda potencial, resposta à fertilização em termos de produção madeireira, crescimento das árvores e viabilidade econômica. Foi verificada uma elevada demanda potencial pelo biossólido em povoamentos de eucaliptos localizados a curtas distâncias de transporte rodoviário no entorno da RMSP. Verificou-se também que o biossólido, complementado com P e K minerais no plantio, acelerou a ritmo de crescimento das árvores, aumentou o nível de produção madeireira e reduziu o ciclo de produção de Eucalyptus grandis em proporções semelhantes às observadas para a fertilização mineral convencional. Na avaliação aos 99 meses de idade, foi verificado que a maior dose de biossólido (40 Mg ha-1) não resultou na maior produção de madeira. Se considerada a diferença estatística entre as curvas de crescimento, os modelos testados podem ser divididos em apenas dois grupos: (i) testemunha e dose de 10 Mg ha-1; e (ii) demais tratamentos. A análise econômica (valor presente líquido anualizado e a taxa de juros de 12% ao ano) recomenda a dose de 5 Mg ha-1, com complementação com K mineral no plantio, se utilizado como critério de definição de corte a escolha da idade que maximiza o incremento médio anual em cada tratamento. Para as condições do trabalho concluiu-se que o biossólido não substitui totalmente a fertilização mineral convencional. Economicamente, confirmou-se a expectativa de que elevadas taxas de aplicação do biossólido são inviáveis, devido principalmente à alta umidade natural desse material que encarece significativamente o transporte. / This work evaluates the use of the residual sludge (biosolids) produced by sewage treatment units located in the Metropolitan Region of the City of São Paulo (MRSP) as a fertilizer in Eucalyptus grandis forest plantations. The aspects studied were potential demand, wood production response to the fertilization, trees growth and economic viability. A high level of potential demand was observed for the biosolids on forest eucalyptus plantations located at short ground transportation distances in the MRSP. It was also observed that biosolids, complemented by phosphorous and potassium at the planting stage, increased the growth rate of the trees, resulted in more wood output and reduced the rotation age at levels similar to those observed for conventional mineral fertilization. When evaluated 99 months after planting, it was observed that the highest dosage of biosolids did not result on the highest wood production output. The adjusted models can be separated in only two groups according to the statistical differences among them: (i) control and dosage 10 Mg ha-1; and (ii) all other treatments. The economic analysis (annualized net present value at 12% return rate) recommended dosage 5 Mg ha-1 complemented with K, for rotation lengths defined by the age that maximizes mean annual increment. The use of biosolids does not substitute totally the use of mineral fertilizers. Economically, it was confirmed that the highest biosolid dosages were not viable, due mainly to its high levels of water content and consequently high transportation cost.

O presente trabalho avaliou o uso do lodo residual (biossólido) produzido nas Estações de Tratamento de Esgoto (ETEs) da Região Metropolitana de São Paulo (RMSP) como fertilizante em florestas de eucaliptos. Os aspectos estudados foram demanda potencial, resposta à fertilização em termos de produção madeireira, crescimento das árvores e viabilidade econômica. Foi verificada uma elevada demanda potencial pelo biossólido em povoamentos de eucaliptos localizados a curtas distâncias de transporte rodoviário no entorno da RMSP. Verificou-se também que o biossólido, complementado com P e K minerais no plantio, acelerou a ritmo de crescimento das árvores, aumentou o nível de produção madeireira e reduziu o ciclo de produção de Eucalyptus grandis em proporções semelhantes às observadas para a fertilização mineral convencional. Na avaliação aos 99 meses de idade, foi verificado que a maior dose de biossólido (40 Mg ha-1) não resultou na maior produção de madeira. Se considerada a diferença estatística entre as curvas de crescimento, os modelos testados podem ser divididos em apenas dois grupos: (i) testemunha e dose de 10 Mg ha-1; e (ii) demais tratamentos. A análise econômica (valor presente líquido anualizado e a taxa de juros de 12% ao ano) recomenda a dose de 5 Mg ha-1, com complementação com K mineral no plantio, se utilizado como critério de definição de corte a escolha da idade que maximiza o incremento médio anual em cada tratamento. Para as condições do trabalho concluiu-se que o biossólido não substitui totalmente a fertilização mineral convencional. Economicamente, confirmou-se a expectativa de que elevadas taxas de aplicação do biossólido são inviáveis, devido principalmente à alta umidade natural desse material que encarece significativamente o transporte. / This work evaluates the use of the residual sludge (biosolids) produced by sewage treatment units located in the Metropolitan Region of the City of São Paulo (MRSP) as a fertilizer in Eucalyptus grandis forest plantations. The aspects studied were potential demand, wood production response to the fertilization, trees growth and economic viability. A high level of potential demand was observed for the biosolids on forest eucalyptus plantations located at short ground transportation distances in the MRSP. It was also observed that biosolids, complemented by phosphorous and potassium at the planting stage, increased the growth rate of the trees, resulted in more wood output and reduced the rotation age at levels similar to those observed for conventional mineral fertilization. When evaluated 99 months after planting, it was observed that the highest dosage of biosolids did not result on the highest wood production output. The adjusted models can be separated in only two groups according to the statistical differences among them: (i) control and dosage 10 Mg ha-1; and (ii) all other treatments. The economic analysis (annualized net present value at 12% return rate) recommended dosage 5 Mg ha-1 complemented with K, for rotation lengths defined by the age that maximizes mean annual increment. The use of biosolids does not substitute totally the use of mineral fertilizers. Economically, it was confirmed that the highest biosolid dosages were not viable, due mainly to its high levels of water content and consequently high transportation cost.

Esta tese examina o problema de detecção de conectividade entre séries temporais no sentido de Granger no caso em que a natureza não linear das interações não permite sua determinação por meio de modelos auto-regressivos lineares vetoriais. Mostra-se que é possível realizar esta detecção com auxílio dos chamados métodos de Kernel, que se tornaram populares em aprendizado por máquina (\'machine learning\') já que tais métodos permitem definir formas generalizadas de teste de Granger, coerência parcial direcionada e função de transferência direcionada. Usando simulações, mostram-se alguns exemplos de detecção nos quais fica também evidente que resultados assintóticos deduzidos originalmente para estimadores lineares podem ser generalizados de modo análogo, mostrando-se válidos no presente contexto kernelizado. / This work examines the connectivity detection problem between time series in the Granger sense when the nonlinear nature of interactions determination is impossible via linear vector autoregressive models, but is, nonetheless, feasible with the aid of the so-called Kernel methods that are popular in machine learning. The kernelization approach allows defining generalised versions for Granger tests, partial directed coherence and directed transfer function, which the simulation of some examples shows that the asymptotic detection results originally deducted for linear estimators, can also be employed under kernelization if suitably adapted.

Stavové modely jsou neobyčejně užitečné v mnoha inženýrských a vědeckých oblastech. Jejich atraktivita vychází především z toho faktu, že poskytují obecný nástroj pro popis široké škály dynamických systémů reálného světa. Nicméně, z důvodu jejich obecnosti, přidružené úlohy inference parametrů a stavů jsou ve většině praktických situacích nepoddajné. Tato dizertační práce uvažuje dvě zvláště důležité třídy nelineárních a ne-Gaussovských stavových modelů: podmíněně konjugované stavové modely a Markovsky přepínající nelineární modely. Hlavní rys těchto modelů spočívá v tom, že---navzdory jejich nepoddajnosti---obsahují poddajnou podstrukturu. Nepoddajná část požaduje abychom využily aproximační techniky. Monte Carlo výpočetní metody představují teoreticky a prakticky dobře etablovaný nástroj pro řešení tohoto problému. Výhoda těchto modelů spočívá v tom, že poddajná část může být využita pro zvýšení efektivity Monte Carlo metod tím, že se uchýlíme k Rao-Blackwellizaci. Konkrétně, tato doktorská práce navrhuje dva Rao-Blackwellizované částicové filtry pro identifikaci buďto statických anebo časově proměnných parametrů v podmíněně konjugovaných stavových modelech. Kromě toho, tato práce adoptuje nedávnou particle Markov chain Monte Carlo metodologii pro návrh Rao-Blackwellizovaných částicových Gibbsových jader pro vyhlazování stavů v Markovsky přepínajících nelineárních modelech. Tyto jádra jsou posléze použity pro inferenci parametrů metodou maximální věrohodnosti v uvažovaných modelech. Výsledné experimenty demonstrují, že navržené algoritmy překonávají příbuzné techniky ve smyslu přesnosti odhadu a výpočetního času.

<div>Stoichiometric air-fuel ratio (AFR) and air/EGR flow control are essential control problems in today’s advanced spark-ignited (SI) engines to enable effective application of the three-way-catalyst (TWC) and generation of required torque. External exhaust gas recirculation (EGR) can be used in SI engines to help mitigate knock, reduce enrichment and improve efficiency[1 ]. However, the introduction of the EGR system increases the complexity of stoichiometric engine-out lambda and torque management, particularly for high BMEP commercial vehicle applications. This thesis develops advanced frameworks for sensing and control architecture designs to enable robust air handling system management, stoichiometric cylinder air-fuel ratio (AFR) control and three-way-catalyst emission control.</div><div><br></div><div><div>The first work in this thesis derives a physically-based, control-oriented model for turbocharged SI engines utilizing cooled EGR and flexible VVA systems. The model includes the impacts of modulation to any combination of 11 actuators, including the throttle valve, bypass valve, fuel injection rate, waste-gate, high-pressure (HP) EGR, low-pressure (LP) EGR, number of firing cylinders, intake and exhaust valve opening and closing timings. A new cylinder-out gas composition estimation method, based on the inputs’ information of cylinder charge flow, injected fuel amount, residual gas mass and intake gas compositions, is proposed in this model. This method can be implemented in the control-oriented model as a critical input for estimating the exhaust manifold gas compositions. A new flow-based turbine-out pressure modeling strategy is also proposed in this thesis as a necessary input to estimate the LP EGR flow rate. Incorporated with these two sub-models, the control-oriented model is capable to capture the dynamics of pressure, temperature and gas compositions in manifolds and the cylinder. Thirteen physical parameters, including intake, boost and exhaust manifolds’ pressures, temperatures, unburnt and burnt mass fractions as well as the turbocharger speed, are defined as state variables. The outputs such as flow rates and AFR are modeled as functions of selected states and inputs. The control-oriented model is validated with a high fidelity SI engine GT-Power model for different operating conditions. The novelty in this physical modeling work includes the development and incorporation of the cylinder-out gas composition estimation method and the turbine-out pressure model in the control-oriented model.</div></div><div><br></div><div><div>The second part of the work outlines a novel sensor selection and observer design algorithm for linear time-invariant systems with both process and measurement noise based on <i>H</i>2 optimization to optimize the tradeoff between the observer error and the number of required sensors. The optimization problem is relaxed to a sequence of convex optimization problems that minimize the cost function consisting of the <i>H</i>2 norm of the observer error and the weighted <i>l</i>1 norm of the observer gain. An LMI formulation allows for efficient solution via semi-definite programing. The approach is applied here, for the first time, to a turbo-charged spark-ignited (SI) engine using exhaust gas recirculation to determine the optimal sensor sets for real-time intake manifold burnt gas mass fraction estimation. Simulation with the candidate estimator embedded in a high fidelity engine GT-Power model demonstrates that the optimal sensor sets selected using this algorithm have the best <i>H</i>2 estimation performance. Sensor redundancy is also analyzed based on the algorithm results. This algorithm is applicable for any type of modern internal combustion engines to reduce system design time and experimental efforts typically required for selecting optimal sensor sets.</div></div><div><br></div><div><div>The third study develops a model-based sensor selection and controller design framework for robust control of air-fuel-ratio (AFR), air flow and EGR flow for turbocharged stoichiometric engines using low pressure EGR, waste-gate turbo-charging, intake throttling and variable valve timing. Model uncertainties, disturbances, transport delays, sensor and actuator characteristics are considered in this framework. Based on the required control performance and candidate sensor sets, the framework synthesizes an H1 feedback controller and evaluates the viability of the candidate sensor set through analysis of the structured</div><div>singular value μ of the closed-loop system in the frequency domain. The framework can also be used to understand if relaxing the controller performance requirements enables the use of a simpler (less costly) sensor set. The sensor selection and controller co-design approach is applied here, for the first time, to turbo-charged engines using exhaust gas circulation. High fidelity GT-Power simulations are used to validate the approach. The novelty of the work in this part can be summarized as follows: (1) A novel control strategy is proposed for the stoichiometric SI engines using low pressure EGR to simultaneously satisfy both the AFR and air/EGR-path control performance requirements; (2) A parametrical method to simultaneously select the sensors and design the controller is first proposed for the internal combustion engines.</div></div><div><br></div><div><div>In the fourth part of the work, a novel two-loop estimation and control strategy is proposed to reduce the emission of the three-way-catalyst (TWC). In the outer loop, an FOS estimator consisting of a TWC model and an extended Kalman-filter is used to estimate the current TWC fractional oxygen state (FOS) and a robust controller is used to control the TWC FOS by manipulating the desired engine λ. The outer loop estimator and controller are combined with an existing inner loop controller. The inner loop controller controls the engine λ based on the desired λ value and the control inaccuracies are considered and compensated by the outer loop robust controller. This control strategy achieves good emission reduction performance and has advantages over the constant λ control strategy and the conventional two-loop switch-type control strategy.</div></div>

[pt] O objetivo desta dissertação é comparar através de um estudo de simulação diferentes estimadores de modelos não-lineares. Nós consideramos neste trabalho o estimador não-linear de mínimos quadrados em dois estágios (NL2SLS), o estimador não-linear de máxima verossimilhança de informação limitada (LIML) e o estimador com função controle (CF). Os resultados mostram que os estimadores CF e LIML possuem em geral uma performance superior ao do NL2SLS para os modelos selecionados. O trabalho considera uma aplicação de uma Curva de Phillips não-linear para a Economia Brasileira. / [en] The aim of this dissertation is to compare, in a simulation study, different nonlinear estimators for selected models. We consider the two-stage nonlinear least-squares (NL2SLS), the nonlinear limited information maximum likelihood (LIML), and the control function (CF) estimator. Our results show that usually either CF or LIML estimators perform better than the NL2SLS estimator for the selected models. In an application with real data, we consider the estimation a nonlinear Phillips Curve for Brazilian economy.