Neste trabalho são apresentadas estratégias para a estimação, em processos químicos, de estados, parâmetros e covariâncias do ruído de processo e das medidas que são testadas com dados experimentais. Para a estimação de estados e parâmetros foram implementadas desde a técnica mais tradicional, o filtro estendido de Kalman (EKF) até as mais modernas da literatura, como o filtro de Kalman Unscented (UKF) e o Moving Horizon Estimator (MHE). A técnica Autocovariance Least-Squares (ALS) permite a estimação das matrizes de covariância do processo e das medidas a partir dos estados medidos dos processos analisados. Três processos foram analisados com as técnicas citadas: a reação de hidrólise de anidrido acético, o aquecimento de um reator de polimerização completamente carregado (sem iniciador) e por fim oito reações diferentes de polimerização em emulsão. Os resultados mostraram que uma sintonia por tentativa e erro para as matrizes de covariância não apresenta um desempenho adequado. Adicionalmente, o UKF mostra um melhor desempenho, quando comparado com o EKF para o monitoramento de processos de polimerização regime em batelada com covariâncias obtidas através de otimização direta. Quando a estimação da covariância com a técnica ALS é implementada e os resultados utilizados em estimadores estocásticos, o desempenho dos estimadores recursivos melhora consideravelmente. Além disso, o MHE mostrou ser uma ferramenta robusta para o monitoramento do coeficiente global de troca térmica (UA) e do calor gerado pela reação para a polimerização em emulsão em regime semi-contínuo. Finalmente, duas características vantajosas da metodologia proposta devem ser destacadas: a independência em relação ao valor inicial para o estado UA e o fato de um único conjunto de matrizes de covariância (quando obtida pela técnica ALS) poder ser utilizado em reações diferentes, sem necessidade de sintonizar novamente as matrizes para cada reação. / In this work, strategies for state, parameter and covariance estimation in chemical processes are presented and tested with experimental data. For state and parameter estimation techniques have been implemented that spread from the traditional Extended Kalman Filter (EKF) to the most modern techniques from literature, such as the Unscented Kalman Filter (UKF) and the Moving Horizon Estimator (MHE). The Autocovariance Least-Squares technique (ALS) allows the covariance matrices of the process and measurement noise to be estimated based on the measured states of the processes analyzed. Three cases were studied using these techniques: the hydrolysis of acetic anhydride, the warming-up stage of a fully charged polymerization reactor (without initiator) to the desired temperature and finally, eight different emulsion polymerization reaction runs. Results showed that determining covariance matrices by trial and error does not lead to an adequate performance. Additionally, the UKF presents a better performance than the EKF for batch polymerization processes with covariance matrices obtained by direct optimization. When the estimation of the covariance is performed by the ALS technique and they are used in a stochastic estimator, the performance of the recursive estimators is considerably improved. Furthermore, the MHE proved to be a robust tool for monitoring the overall heat transfer coefficient (UA) and the heat of reaction for fedbatch emulsion polymerization. Finally, two positive features of the proposed methodology must be highlighted, its low dependency on the initial state condition of UA and the fact that a unique set of covariance matrices (when obtained by the ALS technique) can be used for different reaction runs, without the necessity of tuning the matrices again for each reaction.

Neste trabalho são apresentadas estratégias para a estimação, em processos químicos, de estados, parâmetros e covariâncias do ruído de processo e das medidas que são testadas com dados experimentais. Para a estimação de estados e parâmetros foram implementadas desde a técnica mais tradicional, o filtro estendido de Kalman (EKF) até as mais modernas da literatura, como o filtro de Kalman Unscented (UKF) e o Moving Horizon Estimator (MHE). A técnica Autocovariance Least-Squares (ALS) permite a estimação das matrizes de covariância do processo e das medidas a partir dos estados medidos dos processos analisados. Três processos foram analisados com as técnicas citadas: a reação de hidrólise de anidrido acético, o aquecimento de um reator de polimerização completamente carregado (sem iniciador) e por fim oito reações diferentes de polimerização em emulsão. Os resultados mostraram que uma sintonia por tentativa e erro para as matrizes de covariância não apresenta um desempenho adequado. Adicionalmente, o UKF mostra um melhor desempenho, quando comparado com o EKF para o monitoramento de processos de polimerização regime em batelada com covariâncias obtidas através de otimização direta. Quando a estimação da covariância com a técnica ALS é implementada e os resultados utilizados em estimadores estocásticos, o desempenho dos estimadores recursivos melhora consideravelmente. Além disso, o MHE mostrou ser uma ferramenta robusta para o monitoramento do coeficiente global de troca térmica (UA) e do calor gerado pela reação para a polimerização em emulsão em regime semi-contínuo. Finalmente, duas características vantajosas da metodologia proposta devem ser destacadas: a independência em relação ao valor inicial para o estado UA e o fato de um único conjunto de matrizes de covariância (quando obtida pela técnica ALS) poder ser utilizado em reações diferentes, sem necessidade de sintonizar novamente as matrizes para cada reação. / In this work, strategies for state, parameter and covariance estimation in chemical processes are presented and tested with experimental data. For state and parameter estimation techniques have been implemented that spread from the traditional Extended Kalman Filter (EKF) to the most modern techniques from literature, such as the Unscented Kalman Filter (UKF) and the Moving Horizon Estimator (MHE). The Autocovariance Least-Squares technique (ALS) allows the covariance matrices of the process and measurement noise to be estimated based on the measured states of the processes analyzed. Three cases were studied using these techniques: the hydrolysis of acetic anhydride, the warming-up stage of a fully charged polymerization reactor (without initiator) to the desired temperature and finally, eight different emulsion polymerization reaction runs. Results showed that determining covariance matrices by trial and error does not lead to an adequate performance. Additionally, the UKF presents a better performance than the EKF for batch polymerization processes with covariance matrices obtained by direct optimization. When the estimation of the covariance is performed by the ALS technique and they are used in a stochastic estimator, the performance of the recursive estimators is considerably improved. Furthermore, the MHE proved to be a robust tool for monitoring the overall heat transfer coefficient (UA) and the heat of reaction for fedbatch emulsion polymerization. Finally, two positive features of the proposed methodology must be highlighted, its low dependency on the initial state condition of UA and the fact that a unique set of covariance matrices (when obtained by the ALS technique) can be used for different reaction runs, without the necessity of tuning the matrices again for each reaction.

<p>This doctoral thesis presents new ideas and research results on control of marine electric power system.</p><p>The main motivation for this work is the development of a control system, power management system (PMS) capable to improve the system robustness to blackout, handle major power system faults, minimize the operational cost and keep the power system machinery components under minimal stress in all operational conditions.</p><p>Today, the electric marine power system tends to have more system functionality implemented in integrated automation systems. The present state of the art type of tools and methods for analyzing marine power systems do only to a limited extent utilize the increased knowledge available within each of the mechanical and electrical engineering disciplines.</p><p>As the propulsion system is typically consisted of the largest consumers on the vessel, important interactions exists between the PMS and vessel propulsion system. These are interacted through the dynamic positioning (DP) controller, thrust allocation algorithm, local thruster controllers, generators' local frequency and voltage controllers. The PMS interacts with the propulsion system through the following main functions: available power static load control, load rate limiting control and blackout prevention control (i.e. fast load reduction). These functions serve to prevent the blackout and to ensure that the vessel will always have enough power.</p><p>The PMS interacts with other control systems in order to prevent a blackout and to minimize operational costs. The possibilities to maximize the performance of the vessel, increase the robustness to faults and decrease a component wear-out rate are mainly addressed locally for the individual control systems. The solutions are mainly implicative (for e.g. local thruster control, or DP thrust allocation), and attention has not been given on the interaction between these systems, the power system and PMS. Some of the questions that may arise regarding the system interactions, are as follows: how the PMS functionality may affect a local thruster control, how the local thruster control may affect the power system performance, how some consumers may affect the power system performance in normal operations and thus affect other consumers, how the power system operation may affect the susceptibility to faults and blackout, how various operating and weather conditions may affect the power system performance and thus propulsion performance though the PMS power limiting control, how propulsion performance may affect the overall vessel performance, which kind of faults can be avoided if the control system is re-structured, how to minimize the operational costs and to deal with the conflicting goals. This PhD thesis aims to provide answers to such questions.</p><p>The main contributions of this PhD thesis are:</p><p>− A new observer-based fast load reduction system for the blackout prevention control has been proposed. When compared to the existing fast load reduction systems, the proposed controller gives much faster blackout detection rate, high reliability in the detection and faster and more precise load reduction (within 150 miliseconds).</p><p>− New advanced energy management control strategies for reductions in the operational costs and improved fuel economy of the vessel.</p><p>− Load limiting controllers for the reduction of thruster wear-out rate. These controllers are based on the probability of torque loss, real-time torque loss and the thruster shaft</p><p>accelerations. The controllers provide means of redistributing thrust from load fluctuating thrusters to less load fluctuating ones, and may operate independently of the thrust allocation system. Another solution is also proposed where the load limiting controller based on thrust losses is an integrated part of DP thrust allocation algorithm.</p><p>− A new concept of totally integrated thrust allocation system, local thruster control and power system. These systems are integrated through PMS functionality which is contained within each thruster PLC, thereby distributed among individual controllers, and independent of the communications and dedicated controllers.</p><p>− Observer-based inertial controller and direct torque-loss controller (soft anti-spin controller) with particular attention to the control of machine wear-out rate. These controller contribute to general shaft speed control of electrical thrusters, generators and main propulsion prime movers.</p><p>The proposed controllers, estimators and concepts are demonstrated through time-domain simulations performed in MATLAB/SIMULINK. The selected data are typical for the required applications and may differ slightly for the presented cases.</p>

This doctoral thesis presents new ideas and research results on control of marine electric power system. The main motivation for this work is the development of a control system, power management system (PMS) capable to improve the system robustness to blackout, handle major power system faults, minimize the operational cost and keep the power system machinery components under minimal stress in all operational conditions. Today, the electric marine power system tends to have more system functionality implemented in integrated automation systems. The present state of the art type of tools and methods for analyzing marine power systems do only to a limited extent utilize the increased knowledge available within each of the mechanical and electrical engineering disciplines. As the propulsion system is typically consisted of the largest consumers on the vessel, important interactions exists between the PMS and vessel propulsion system. These are interacted through the dynamic positioning (DP) controller, thrust allocation algorithm, local thruster controllers, generators' local frequency and voltage controllers. The PMS interacts with the propulsion system through the following main functions: available power static load control, load rate limiting control and blackout prevention control (i.e. fast load reduction). These functions serve to prevent the blackout and to ensure that the vessel will always have enough power. The PMS interacts with other control systems in order to prevent a blackout and to minimize operational costs. The possibilities to maximize the performance of the vessel, increase the robustness to faults and decrease a component wear-out rate are mainly addressed locally for the individual control systems. The solutions are mainly implicative (for e.g. local thruster control, or DP thrust allocation), and attention has not been given on the interaction between these systems, the power system and PMS. Some of the questions that may arise regarding the system interactions, are as follows: how the PMS functionality may affect a local thruster control, how the local thruster control may affect the power system performance, how some consumers may affect the power system performance in normal operations and thus affect other consumers, how the power system operation may affect the susceptibility to faults and blackout, how various operating and weather conditions may affect the power system performance and thus propulsion performance though the PMS power limiting control, how propulsion performance may affect the overall vessel performance, which kind of faults can be avoided if the control system is re-structured, how to minimize the operational costs and to deal with the conflicting goals. This PhD thesis aims to provide answers to such questions. The main contributions of this PhD thesis are: − A new observer-based fast load reduction system for the blackout prevention control has been proposed. When compared to the existing fast load reduction systems, the proposed controller gives much faster blackout detection rate, high reliability in the detection and faster and more precise load reduction (within 150 miliseconds). − New advanced energy management control strategies for reductions in the operational costs and improved fuel economy of the vessel. − Load limiting controllers for the reduction of thruster wear-out rate. These controllers are based on the probability of torque loss, real-time torque loss and the thruster shaft accelerations. The controllers provide means of redistributing thrust from load fluctuating thrusters to less load fluctuating ones, and may operate independently of the thrust allocation system. Another solution is also proposed where the load limiting controller based on thrust losses is an integrated part of DP thrust allocation algorithm. − A new concept of totally integrated thrust allocation system, local thruster control and power system. These systems are integrated through PMS functionality which is contained within each thruster PLC, thereby distributed among individual controllers, and independent of the communications and dedicated controllers. − Observer-based inertial controller and direct torque-loss controller (soft anti-spin controller) with particular attention to the control of machine wear-out rate. These controller contribute to general shaft speed control of electrical thrusters, generators and main propulsion prime movers. The proposed controllers, estimators and concepts are demonstrated through time-domain simulations performed in MATLAB/SIMULINK. The selected data are typical for the required applications and may differ slightly for the presented cases.

<p>An emerging technology in the field of transient thermal management is thermal energy storage, or TES, which enables temporary, on-demand heat rejection via storage as latent heat in a phase-change material.  Latent TES devices have enabled advances in many thermal management applications, including peak load shifting for reducing energy demand and cost of HVAC systems and providing supplemental heat rejection in transient thermal management systems.  However, the design of a transient thermal management system with integrated storage comprises many challenges which are yet to be solved.  For example, design approaches and performance metrics for determining the optimal dimensions of the TES device have only recently been studied.  Another area of active research is estimation of the internal temperature state of the device, which can be difficult to directly measure given the transient nature of the thermal storage process.  Furthermore, in contrast to the three main functions of a thermal-fluid system--heat addition, thermal transport, and heat rejection--thermal storage introduces the need for active, real-time control and automated decision making for managing the operation of the thermal storage device. </p> <p>In this thesis, I present the design process for integrating thermal energy storage into a single-phase thermal management system for rejecting transient heat loads, including design of the TES device, state estimation and control algorithm design, and validation in both simulation and experimental environments. Leveraging a reduced-order finite volume simulation model of a plate-fin TES device, I develop a design approach which involves a transient simulation-based design optimization to determine the required geometric dimensions of the device to meet transient performance objectives while maximizing power density.  The optimized TES device is integrated into a single-phase thermal-fluid testbed for experimental testing.  Using the finite volume model and feedback from thermocouples embedded in the device, I design and experimentally validate a state estimator based on the state-dependent Riccati equation approach for determining the internal temperature distribution to a high degree of accuracy.  Real-time knowledge of the internal temperature state is critical for making control decisions; to manage the operation of the TES device in the context of a transient thermal management system, I design and test, both in simulation and experimentally, a logic-based control strategy that uses fluid temperature measurements and estimates of the TES state to make real-time control decisions to meet critical thermal management objectives. Together, these advances demonstrate the potential of thermal energy storage technology as a component of thermal management systems and the feasibility of logic-based control strategies for real-time control of thermal management objectives.</p>