This thesis models and analyzes an in-situ method for measuring the density of the thermosphere at low Earth orbit (LEO) altitudes in real time. As satellites orbit in the thermosphere, the sparse yet present air perturbs their orbits via the drag force. The drag force is poorly characterized and has a significant effect at LEO altitudes relative to other forces, making this perturbation force one of the greatest uncertainties in LEO orbit propagation. A steadily increasing number of satellites orbit at LEO altitudes, so for safety, it is critical to accurately track these satellites to avoid collisions. Therefore, better knowledge of the drag force is required. The drag force depends directly on the air mass density in the thermosphere, and current knowledge of the thermospheric density is limited. Models exist to describe the variations in density over time, but due to the many unpredictable factors which affect the thermosphere, the best of these models are only accurate to within 10%. Also, currently available techniques to measure the thermospheric density can only return time-averaged measurements, which causes inaccuracies in orbit propagation due to local density variations. Some planned in-situ density measurement missions rely on measuring acceleration caused by the drag force, but this requires a highly accurate accelerometer to be able to separate the drag force from other stronger forces acting on a satellite. The Satellite Producing Aerodynamic Torque to Understand LEO Atmosphere (SPATULA) concept was introduced as an alternative method, which infers density based on measurements of the drag torque. In the rotational regime, drag produces the strongest torque at LEO altitudes by far, making it possible to acquire accurate density measurements with inexpensive, commercially available sensors and actuators on a SPATULA spacecraft. This thesis expands upon a preliminary study of the SPATULA concept. A SPATULA spacecraft's dynamics are modeled in three dimensions, and a novel method is introduced for modeling the dependence of external torques on the geometry and attitude of the spacecraft. In addition to the dynamics model, discrete-time algorithms for guidance, system state filtering, attitude control, and density estimation are developed for the six degrees of freedom case. The MathWorks tools MATLAB and Simulink are used to simulate the physics and system models. The simulations are used to evaluate the performance of the SPATULA system's density measurements and compare them to conventional methods. It is found that the accuracy and bandwidth of the SPATULA system have a significant dependence on the assumed accuracy of the torque models in the system's filter. When the bandwidth is set to avoid significant phase shift errors, the SPATULA system can produce real-time measurements of density accurate over a minimum time scale of about 60 seconds, and the density error has a standard deviation of about 2 x 10^-14 kg/m^3. This accuracy is about 6 times better than the best thermospheric models, and it is also better than reported accuracies of most other density measurement methods. If bandwidth is sacrificed, the density error standard deviation can be decreased by a factor of 4. This introduces additional error due to phase shift delays, but these can be corrected with signal processing techniques. With the higher accuracy, the SPATULA system loses its real-time ability, but the data it produces would still provide excellent insight for improving thermospheric models. With high accuracy and low cost, the SPATULA concept is a promising path to pursue toward improving thermospheric density knowledge. / Master of Science / This thesis models and analyzes a method for measuring the density of the upper atmosphere in real time directly onboard a satellite. As low Earth orbit (LEO) satellites orbit at low altitudes, the sparse yet present atmosphere changes their orbits via the drag force. The drag force is poorly characterized and has a significant effect at LEO altitudes relative to other forces, making this perturbation force one of the greatest uncertainties in LEO orbit prediction. A steadily increasing number of satellites orbit at LEO altitudes, so for safety, it is critical to accurately track and predict the orbits of these satellites to avoid collisions. Therefore, better knowledge of the drag force is required. The drag force depends directly on air density, and current knowledge of the upper atmospheric density is limited. Models exist to describe the variations in density over time, but due to the many unpredictable factors which affect the atmosphere, the best of these models are only accurate to within 10%. Also, currently available techniques to measure the upper atmospheric density can only return time-averaged measurements, which causes inaccuracies in orbit prediction due to local density variations. Some planned density measurement missions rely on measuring acceleration caused by the drag force, but this requires a highly accurate accelerometer to be able to separate the drag force from other stronger forces acting on a satellite. The Satellite Producing Aerodynamic Torque to Understand LEO Atmosphere (SPATULA) concept was introduced as an alternative method, which infers density based on measurements of the drag torque. Drag produces the strongest torque at LEO altitudes by far, making it possible to acquire accurate density measurements with inexpensive, commercially available parts on a SPATULA spacecraft. This thesis expands upon a preliminary study of the SPATULA concept. A SPATULA spacecraft's motion and rotation is modeled in three dimensions, and a novel method is introduced for modeling the dependence of external torques on the geometry and orientation of the spacecraft. In addition to the dynamics model, algorithms that could be implemented on a satellite's computer are developed for determining the best orientation, estimating the state of the system, controlling the orientation, and estimating density. The MathWorks tools MATLAB and Simulink are used to simulate the physics and system models. The simulations are used to evaluate the performance of the SPATULA system's density measurements and compare them to conventional methods. It is found that the accuracy and bandwidth of the SPATULA system have a significant dependence on the assumed accuracy of the torque models used by the system. When a high bandwidth is used to avoid problems associated with low bandwidth, the SPATULA system can produce real-time measurements of density accurate over a minimum time scale of about 60 seconds, and the density error has a standard deviation of about 2 x 10^-14 kg/m^2. This accuracy is about 6 times better than the best upper atmospheric models, and it is also better than reported accuracies of most other density measurement methods. If bandwidth is sacrificed, the density error standard deviation can be decreased by a factor of 4. This introduces additional error due to delayed measurements of quickly varying components of the density, but these can be corrected with signal processing techniques. With the higher accuracy, the SPATULA system loses its real-time ability, but the data it produces would still provide excellent insight for improving atmospheric density models. With high accuracy and low cost, the SPATULA concept is a promising path to pursue toward improving density knowledge.

Os motores de indução trifásicos são largamente usados em vários setores da indústria. O dimensionamento da potência adequada de um motor de indução ou assíncrono trifásico, em função do comportamento das cargas acopladas ao eixo, continua em alguns casos impreciso pela falta de conhecimento mais completo do comportamento das cargas. A proposta deste trabalho consiste na utilização de sistemas Fuzzy como uma alternativa aos métodos tradicionais para levantamento do comportamento de carga e, em processos de controle, onde há a necessidade de conhecimento do comportamento do conjugado aplicado ao eixo do motor, enfocando diversos tipos de cargas encontrados em indústrias. Resultados de simulações são apresentados para validar a proposta deste trabalho. / The three phase induction motors are widely used in all industrial sectors. The selection procedure of the motor for a particular application is sometimes inaccurate due to the lack of complete knowledge about the load connected to its shaft. The proposal of this work consists of using Fuzzy system as an alternative tool to the classical methods for extraction of the load behavior and, in control process, where knowledge of the torque behavior applied to the motor shaft are need, focusing several types of loads found in industries. Simulation results are presented to validate the proposal of this work.

Este trabalho apresenta um método de estimativa de torque do joelho baseado em sinais eletromiográficos (EMG) durante terapia de reabilitação robótica. Os EMGs, adquiridos de cinco músculos envolvidos no movimento de flexão e extensão do joelho, são processados para encontrar as ativações musculares. Em seguida, mediante um modelo simples de contração muscular, são calculadas as forças e, usando a geometria da articulação, o torque do joelho. As funções de ativação e contração musculares possuem parâmetros limitados que devem ser calibrados para cada usuário, sendo o ajuste feito mediante a minimização do erro entre o torque estimado e o torque medido na articulação usando a dinâmica inversa. São comparados dois métodos iterativos para funções não-lineares como técnicas de otimização restrita para a calibração dos parâmetros: Gradiente Descendente e Quasi-Newton. O processamento de sinais, calibração de parâmetros e cálculo de torque estimado foram desenvolvidos no software MATLAB®; o cálculo de torque medido foi feito no software OpenSim com sua ferramenta de dinâmica inversa. / This work presents a method for knee torque estimation based on electromyographic signals (EMG) during robotic rehabilitation therapy. EMG, taken from five muscles acting during flexion and extension movements of the knee joint, are processed to get the muscle activations. Then, through a simple model of muscle contraction, the forces are computed and knee torque estimated using the joint geometry. Muscle activation and muscle contraction functions have bounded parameters to be adjusted for each user. This adjustment is made by minimizing the error between the estimated torque and the measured torque in the joint computed via inverse dynamics. Two iterative methods for constrained nonlinear optimization are compared, escending Gradient and Quasi-Newton. Signal processing, parameters calibration and estimated torque calculation are developed in the MATLAB® software. Measured torque calculation is performed on OpenSim software using the dynamic inverse tool.

<p>The importance of control systems and diagnostics in vehicles are increasing and has resulted in several new methods to calculate better control signals. The performance can be increased by calculating these signals close to optimum, but that also require more and precise information regarding the system.</p><p>One of the wanted control signals are the crankshaft torque and the thesis presents two different methods to estimate this torque using engine speed variations. These methods are Modeling of the Crankshaft and Frequency Analysis. The methods are evaluated and implemented on for a four cylinder SAAB engine. Measurements are made in an engine test cell as well as a vehicle.</p><p>The results show that the Modeling of the Crankshaft method does not produce a satisfying estimation, with a difference of about 200% between estimated and calculated torque. On the other hand, the Frequency Analysis provides an accurate estimation of both mean and instantaneous indicated torque, with a maximum difference of ±20% between estimated and calculated torque.</p>

<p>The current interest regarding how to stop the global warming has put focus on the automobile industry and forced them to produce vehicles/engines that are more environmental friendly. This has led to the development of increasingly complex controlsystem of the engines. The introduction of common-rail systems in regular automotives increased the demand of physical models that in an accurate way can describe the complex cycle within the combustion chamber. With these models implemented it is possible to test new strategies on engine steering in a cost- and time efficient way.</p><p>The main purpose with this report is to, build our own model based on the existing theoretical models in diesel engine combustion. The model has then been evaluated in a simulation environment using Matlab/Simulink. The model that has been implemented is a multi-zone type and is able to handle multiple injections.</p><p>The model that this thesis results in can in a good way predict both pressure and torque generated in the cylinder. More investigation in how the parameter settings behave in other work-points must be done to enhance the models accuracy. There is also some work left to do in the validation of the model but to make this possible more experimental data must be accessible.</p>

Este trabalho apresenta um método de estimativa de torque do joelho baseado em sinais eletromiográficos (EMG) durante terapia de reabilitação robótica. Os EMGs, adquiridos de cinco músculos envolvidos no movimento de flexão e extensão do joelho, são processados para encontrar as ativações musculares. Em seguida, mediante um modelo simples de contração muscular, são calculadas as forças e, usando a geometria da articulação, o torque do joelho. As funções de ativação e contração musculares possuem parâmetros limitados que devem ser calibrados para cada usuário, sendo o ajuste feito mediante a minimização do erro entre o torque estimado e o torque medido na articulação usando a dinâmica inversa. São comparados dois métodos iterativos para funções não-lineares como técnicas de otimização restrita para a calibração dos parâmetros: Gradiente Descendente e Quasi-Newton. O processamento de sinais, calibração de parâmetros e cálculo de torque estimado foram desenvolvidos no software MATLAB®; o cálculo de torque medido foi feito no software OpenSim com sua ferramenta de dinâmica inversa. / This work presents a method for knee torque estimation based on electromyographic signals (EMG) during robotic rehabilitation therapy. EMG, taken from five muscles acting during flexion and extension movements of the knee joint, are processed to get the muscle activations. Then, through a simple model of muscle contraction, the forces are computed and knee torque estimated using the joint geometry. Muscle activation and muscle contraction functions have bounded parameters to be adjusted for each user. This adjustment is made by minimizing the error between the estimated torque and the measured torque in the joint computed via inverse dynamics. Two iterative methods for constrained nonlinear optimization are compared, escending Gradient and Quasi-Newton. Signal processing, parameters calibration and estimated torque calculation are developed in the MATLAB® software. Measured torque calculation is performed on OpenSim software using the dynamic inverse tool.

The importance of control systems and diagnostics in vehicles are increasing and has resulted in several new methods to calculate better control signals. The performance can be increased by calculating these signals close to optimum, but that also require more and precise information regarding the system. One of the wanted control signals are the crankshaft torque and the thesis presents two different methods to estimate this torque using engine speed variations. These methods are Modeling of the Crankshaft and Frequency Analysis. The methods are evaluated and implemented on for a four cylinder SAAB engine. Measurements are made in an engine test cell as well as a vehicle. The results show that the Modeling of the Crankshaft method does not produce a satisfying estimation, with a difference of about 200% between estimated and calculated torque. On the other hand, the Frequency Analysis provides an accurate estimation of both mean and instantaneous indicated torque, with a maximum difference of ±20% between estimated and calculated torque.

The current interest regarding how to stop the global warming has put focus on the automobile industry and forced them to produce vehicles/engines that are more environmental friendly. This has led to the development of increasingly complex controlsystem of the engines. The introduction of common-rail systems in regular automotives increased the demand of physical models that in an accurate way can describe the complex cycle within the combustion chamber. With these models implemented it is possible to test new strategies on engine steering in a cost- and time efficient way. The main purpose with this report is to, build our own model based on the existing theoretical models in diesel engine combustion. The model has then been evaluated in a simulation environment using Matlab/Simulink. The model that has been implemented is a multi-zone type and is able to handle multiple injections. The model that this thesis results in can in a good way predict both pressure and torque generated in the cylinder. More investigation in how the parameter settings behave in other work-points must be done to enhance the models accuracy. There is also some work left to do in the validation of the model but to make this possible more experimental data must be accessible.

Os motores de indução trifásicos são largamente usados em vários setores da indústria. O dimensionamento da potência adequada de um motor de indução ou assíncrono trifásico, em função do comportamento das cargas acopladas ao eixo, continua em alguns casos impreciso pela falta de conhecimento mais completo do comportamento das cargas. A proposta deste trabalho consiste na utilização de sistemas Fuzzy como uma alternativa aos métodos tradicionais para levantamento do comportamento de carga e, em processos de controle, onde há a necessidade de conhecimento do comportamento do conjugado aplicado ao eixo do motor, enfocando diversos tipos de cargas encontrados em indústrias. Resultados de simulações são apresentados para validar a proposta deste trabalho. / The three phase induction motors are widely used in all industrial sectors. The selection procedure of the motor for a particular application is sometimes inaccurate due to the lack of complete knowledge about the load connected to its shaft. The proposal of this work consists of using Fuzzy system as an alternative tool to the classical methods for extraction of the load behavior and, in control process, where knowledge of the torque behavior applied to the motor shaft are need, focusing several types of loads found in industries. Simulation results are presented to validate the proposal of this work.

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