This thesis investigates the concept of controlling a CubeSat constellation in low-Earth orbit. Low-Earth orbits are considered because the torque used for satellite control is supplied with magnetorquers, and the closer the satellite is to Earth’s magnetic field the more control gain can be supplied. Also, this is the expected orbit altitude of future CubeSat constellations to enable communications. Controlling a CubeSat relies on attitude determination. This means being able to estimate its attitude relative to a given reference frame. To determine the attitude, we propose to use a star tracker and a Kalman filter. A star tracker scans the stars in the satellite’s view, correlates the object to a database, to return an attitude measurement. The measurement is then processed using the Kalman filter. The attitude estimate is then used as the reference input for the controller. Once the attitude of the satellites is determined, a controller can be implemented; assuming the system is controllable and observable. These parameters are verified by adding enough actuators and sensors, respectively. The novelty of this thesis is constructing a controller that will take three satellites and their attitude estimates and arrange them broadside to a target. For simplicity, the arrangement will be a linear formation, and the target and satellite constellation will all be near-field communication. The goal is to place the satellite constellation in an attitude for an intersatellite link to be established. This is a proposed solution to better budget power and computational constraints associated with CubeSats. In addition to adjusting the topology of the system, a communication method must be considered for the data to be distributed across the system requiring an antenna design to implement the communication method. Both issues are discussed in the thesis; however, the focus is the controller design for attitude control. The control approach is a multi-input multi-output (MIMO) sliding fuzzy controller. The focus of the analysis is attitude control for communication while maintaining the constellation in a linear formation. The results shown this controller to be a valid proof of concept.

The main objective of this work is to design robust, fast, and practical controllers for gantry and tower cranes. The controllers are designed to transfer the load from point to point as fast as possible and, at the same time, the load swing is kept small during the transfer process and completely vanishes at the load destination. Moreover, variations of the system parameters, such as the cable length and the load weight, are also included. Practical considerations, such as the control action power, and the maximum acceleration and velocity, are taken into account. In addition, friction effects are included in the design using a friction-compensation technique. The designed controllers are based on two approaches. In the first approach, a gain-scheduling feedback controller is designed to move the load from point to point within one oscillation cycle without inducing large swings. The settling time of the system is taken to be equal to the period of oscillation of the load. This criterion enables calculation of the controller feedback gains for varying load weight and cable length. The position references for this controller are step functions. Moreover, the position and swing controllers are treated in a unified way. In the second approach, the transfer process and the swing control are separated in the controller design. This approach requires designing two controllers independently: an anti-swing controller and a tracking controller. The objective of the anti-swing controller is to reduce the load swing. The tracking controller is responsible for making the trolley follow a reference position trajectory. We use a PD-controller for tracking, while the anti-swing controller is designed using three different methods: (a) a classical PD controller, (b) two controllers based on a delayed-feedback technique, and (c) a fuzzy logic controller that maps the delayed-feedback controller performance. To validate the designed controllers, an experimental setup was built. Although the designed controllers work perfectly in the computer simulations, the experimental results are unacceptable due to the high friction in the system. This friction deteriorates the system response by introducing time delay, high steady-state error in the trolley and tower positions, and high residual load swings. To overcome friction in the tower-crane model, we estimate the friction, then we apply an opposite control action to cancel it. To estimate the friction force, we assume a mathematical model and estimate the model coefficients using an off-line identification technique using the method of least squares. With friction compensation, the experimental results are in good agreement with the computer simulations. The gain-scheduling controllers transfer the load smoothly without inducing an overshoot in the trolley position. Moreover, the load can be transferred in a time near to the optimal time with small swing angles during the transfer process. With full-state feedback, the crane can reach any position in the working environment without exceeding the system power capability by controlling the forward gain in the feedback loop. For large distances, we have to decrease this gain, which in turn slows the transfer process. Therefore, this approach is more suitable for short distances. The tracking-anti-swing control approach is usually associated with overshoots in the translational and rotational motions. These overshoots increase with an increase in the maximum acceleration of the trajectories . The transfer time is longer than that obtained with the first approach. However, the crane can follow any trajectory, which makes the controller cope with obstacles in the working environment. Also, we do not need to recalculate the feedback gains for each transfer distance as in the gain-scheduling feedback controller. / Ph. D.

No description available.

No description available.

Scheduling trains is a hard problem where current solutions typically create timetables that create undesirable amounts of delay for the trains that use them. This study considers the fact that conventional timetables, which only use fixed intervals to schedule trains, might not be optimal for minimising the delay and travel time of passengers. In this study, we compare this ”simple” timetable with timetables generated via a fuzzy controller which has access to information about the flow of passengers throughout the day. The hypothesis is that this fuzzy controller therefore becomes more ”intelligent”. We evaluate the performance using a custom-built simulator that measures the average delay and travel time of the passengers. We conclude that the fuzzy controller can generate timetables that quickly adapt to passenger demands and show favourable resource usage over the simple timetable. However, more research is needed on the input variables and their usage within the fuzzy controller to further optimise the performance. / Schemaläggning av tåg är ett svårt problem och nuvarande lösningar skapar ofta tidtabeller med oönskade mängder förseningar. Den här rapporten behandlar faktumet att enkla tidtabeller, som enbart använder fasta intervaller för tågens avgång, kanske inte är optimala för att minimera antalet förseningar samt resenärers restid. Den här studien jämför enkla tidtabeller, med fasta intervall, med tidtabeller som skapats av en fuzzy controller som har tillgång till information om passagerarflödet. Hypotesen är att fuzzy controllern på så sätt blir mer intelligent. Rapporten utvärderar hur bra tidtabellerna presterar med hjälp av en simulator som mäter genomsnittlig försening och restid för passagerarna i simulationen. Slutsatsen som dras är att en fuzzy controller kan generera tidtabeller som kan anpassa sig till passagerarflödet samt att denna uppvisar gynnsam resursanvändning i jämförelse med den enkla tidtabellen. Dock framhävs behovet av ytterligare forskning på indatavariabler och dess användning inom fuzzy controllern för att vidare kunna optimera dess prestanda.

Propõe-se um controlador difuso Takagi-Sugeno com índice de desempenho H \'INFINITO\' para regulagem da marcha lenta em motores de ciclo Otto. Obtém-se uma representação difusa do motor de ciclo Otto operando em marcha lenta. Esse modelo é utilizado para a síntese do controlador. O controlador difuso com desempenho H \'INFINITO\' é projetado para rejeitar o efeito de distúrbios de cargas externas sobre a rotação do motor em regime de marcha lenta. As ações de controle, posição da borboleta de aceleração e ponto de ignição, são limitadas a uma faixa de operação específica para a marcha lenta. O controlador projetado apresenta ação de controle por realimentação de estados. Os ganhos de realimentação para cada regra do controlador difuso são obtidos a partir de um problema de otimização formulado através de LMIs. / It is proposed an Otto cicle engine idle speed H \'INFINITE\' Takagi-Sugeno fuzzy control. It is presented an Otto cicle engine idle speed fuzzy model. This model is then used to control design. The H \'INFINITE\' fuzzy control is designed to reject external load disturbance effect at idle speed engine rotation. A specifc idle speed operation range is defined to both actions control, throttle plate position and spark advance. A state feedback control is designed. A LMI optmization problem is used to find the state feedback gains at each fuzzy control rule.

Neste trabalho, a automação de um sistema de pulverização a taxa variada com injeção direta é apresentado. A automação do sistema de pulverização montado em uma bancada laboratorial estática foi baseado em um controlador programável com capacidade de tempo real. Os sistemas de pulverização com injeção direta possibilitam o uso de diferentes agroquímicos em uma mesma aplicação, e adicionalmente reduzem os impactos toxicológico e ambiental relacionados com o preparo e descarte da mistura de agroquímico e água. A automação deste sistema envolve o desenvolvimento de placas de interface, a modelagem do pulverizador e o controle das vazões. Um ambiente de simulação baseado no LabVIEW permitiu que os códigos fonte e as rotinas desenvolvidas fossem utilizadas diretamente no controlador programável, exigindo pouca ou nenhuma modificação. Para regular a vazão de injeção do agroquímico, que é dada por uma bomba de pistão, é utilizado um controlador proporcional-integral (PI). Já para regular a vazão da mistura de agroquímico e água, que é dada por uma válvula de controle proporcional de três vias, são implementados dois controladores: um controlador proporcional-integral-derivativo (PID) e um controlador adaptativo do tipo PID fuzzy por escalonamento de ganho. O desempenho dos controladores implementados são analisados via os resultados do erro de aplicação e das vazões. / In this work, the automation of a direct injection sprayer system for variable rate application of agrochemicals is presented. The automation of the sprayer system assembled on a laboratory static bench is based on a programmable controller with real time capabilities. Variable rate sprayer with direct injection systems allow multiple agrochemical application and additionally reduces the toxicologic and environmental risks associated with the carrier-agrochemical mix preparation and discard. The automation of this system comprises the development of interface boards, the sprayer modeling and the control of flow rates. Using a simulation environment based on LabVIEW, the developed source code and routines could be implemented directly in the programmable controller, requiring few or no changes. For the injection flow rate, which is set by a piston pump, a proportional-integral (PI) controller is used. And, to regulate the carrier-agrochemical mix flow rate, which is set by a three-way proportional control valve, two controllers are used: a proportional-integral-derivative (PID) controller and a fuzzy gain scheduling of PID controller. The performance of the implemented controllers is analyzed via the flow rates and the application error results.

O transporte pneumático de sólidos constitui uma aplicação comum em processos industriais petroquímicos, de mineração, de alimentos e agrícola. Entretanto, devido a limitações de ordem prática, a maioria das aplicações existente envolve o transporte de 1 a 400 toneladas por hora, através de distâncias de até 1000 m. Entre estas limitações, o consumo de potência provavelmente é a mais severa. Um sistema de transporte seguro e que apresente uma redução no consumo de potência pode ser implementado com técnicas não convencionais de controle. Este trabalho descreve a implementação de um controlador difuso em um circuito experimental de 45 mm de diâmetro interno utilizado para transportar sementes de Setaria Itálica ao longo de 21 metros. Informações obtidas com um estudo prévio de identificação de regimes gás - sólido através de redes neurais auto-organizáveis foram utilizadas no projeto do controlador. Os resultados mostraram uma redução significativa de 41%, em média, no consumo de potência requerida para o transporte de uma mesma carga de sólido. / The pneumatic conveying of solids in a gas stream is a recurrent process in petrochemical industries as well as in agricultural, food and mining. However, due to practical limitations the majority of existing systems have capacities ranging from 1 to 400 tones per hour over distances less than 1000 m, mainly because of a high power consumption per transported unit mass. A safe circuit with reduced power consumption can be designed using non-conventional control techniques. This work describes a fuzzy controller implementation for a 45 mm i.d. pneumatic conveying system used to transport Setaria Italica seeds over a distance of 21 m. Data obtained in a previous study about gas-solid flow regime identification through a self-organizing neural network were used in the controller design. The results show that reduction in power consumption can reach 41% when compared with classical non controller transport.

Este trabalho apresenta técnicas de projeto de controle neural e controle difuso para uma plataforma de Stewart acionada hidraulicamente. O modelo dinâmico não linear da plataforma de Stewart com seis graus de liberdade foi desenvolvido no ambiente de sistemas multicorpos ADAMS. Este pacote comercial foi usado para economizar tempo e esforço na modelagem de um sistema mecânico complexo e na programação para obter a resposta no tempo do sistema. A plataforma de Stewart é um manipulador paralelo com alta relação força-peso e acuracidade de posicionamento comparada a manipuladores seriais convencionais. As desvantagens dos mecanismos seriais é que cada articulação suporta o peso da articulação seguinte e mais o objeto a ser manipulado. A plataforma de Stewart tem recebido recentemente considerável interesse de pesquisadores dado o sucesso de suas aplicações e potencial vantagens sobre os manipuladores convencionais. Uma aplicação bastante popular da plataforma de Stewart é o simulador de vôo onde a plataforma executa movimento com acelerações similares àquelas de uma aeronave. Embora muitas pesquisas na literatura tenham dedicado amplo esforço para cinemática, dinâmica e projeto mecânico de manipuladores baseados em plataforma de Stewart, pouca atenção tem sido dada ao problema de controle deste tipo de manipulador. Um esquema de controle difuso e de redes neurais foi adotado para lidar com as não linearidades, distúrbios e incertezas dos parâmetros, e precisão necessária no posicionamento e orientação da plataforma. Redes neurais artificiais e lógica difusa fornecem um paradigma computacional característico e tem demonstrado resultado para uma faixa de problemas práticos onde a técnica computacional convencional não tem sucesso. Em particular, a habilidade do controle neural e do controle difuso para representar mapeamento não linear encoraja o estudo de controle neural e difuso para representar problemas de controle não linear. Resultados de simulação são apresentados, mostrando que as técnicas propostas podem ser usadas na plataforma de Stewart. / This work presents a neural and fuzzy control design technique for a hydraulically driven Stewart platform. The non-linear dynamic model of a Stewart platform with six degrees of freedom was developed in the multibody systems environment ADAMS. This commercial package was used to save time and effort in modelling the complex mechanical system and in the programming to get the time response of the system. The Stewart platform is a parallel manipulator with high force-to-weight ratio and position accuracy compared to conventional serial manipulators. The disadvantage of serial mechanisms is that each link has to support the weigth of all the following links in addition to the object to be supported. The Stewart platform has recently received considerable research interest due to its successful applications and potential advantages over the conventional manipulators. A quite popular application of the Stewart platform is the flight simulator where the platform performs motion with accelerations similar to those of an airplane. Although much of the research in the literature has devoted extensive effort to the kinematics, dynamics and mechanisms design of the Stewart platform-based manipulators, little attention has been paid to the control problem of this type of manipulators. A fuzzy and neural network control scheme was adopted to deal with the nonlinealities, disturbances and uncertainties of the parameters, and required precision in position and orientation the platform. Artificial neural networks and fuzzy logic provide a distinctive computational paradigm and have proven to be effective for a range of practical problems where conventional computation techniques have not succeeded. In particular, the ability of neural and fuzzy control techniques to represent non-linear mappings encourages the study of these techniques to be used for controling complex non-linear control problems. Simulations results are presented, showing that the proposed technique can be used in a Stewart platform.

Este trabalho apresenta uma proposta para o controle da suspensão veicular utilizando o amortecedor magneto-reológico, sendo o controle proposto composto pela associação de duas estratégias de controle, o controle ótimo e o controle fuzzy. O Controle ótimo é utilizado para determinar a força a ser utilizada pelo amortecedor magneto-reológico, e o controle fuzzy é utilizado para determinar a corrente elétrica, a ser utilizada no amortecedor magento-reológico e é obtido considerando o modelo de Mandani. Para o controle fuzzy, são consideradas duas entradas, a velocidade de deslocamento do pistão do amortecedor e a força prevista pelo controle ótimo, e uma saída, a corrente elétrica [A]. Para demonstrar a eficiência do controle proposto são consideradas simulações computacionais, utilizando um modelo matemático não-linear de um quarto de veículo. A análise do desempenho do controle é realizada, considerando excitações provocadas por irregularidades na pista, as irregularidades são representadas por entradas tipo degrau, impulso e senoidal. As simulações computacionais são realizadas, utilizando o Matlab® e o Simulink. Os resultados das simulações demonstram que o controle proposto aumenta a segurança do veículo e melhora sua dirigibilidade, reduzindo o deslocamento vertical do conjunto eixo e roda e o espaço de trabalho do amortecedor, quando comparado como o sistema passivo. Também contribui com o conforto dos passageiros, reduzindo as oscilações da carroceria, mantendo os níveis de aceleração abaixo dos considerados desconfortáveis pela norma BS 6841, 1987. Para verificar o comportamento do controle proposto, diante de incertezas, são realizadas simulações computacionais, considerando a possibilidade de erros paramétricos. As simulações, considerando os erros paramétricos, demonstram que o controle ótimo, mesmo quando sujeito a incertezas, permanece sendo estável e ótimo. / This work presents a proposal for control of vehicular suspension using the magneto-rheological damper, the proposed control is composed by association of two control strategy, the optimal control and the fuzzy control. The optimal control is used to determine the power to be applied by the magneto-rheological damper, and the fuzzy control is used to determine the electric current to be used in the magneto-rheological damper and is obtained considering the Mandani's model. For the fuzzy control two inputs are considered, the velocity of the piston's damper and the force provided by the optimal control, and one output, the electric current [A]. To demonstrate the efficiency of the proposed control, computational simulations are considered using a nonlinear mathematical model for a quarter-car. The performance of the control is analyzed considering excitements provoked by irregularities in the track, the irregularities are represented by entrances step type, pulse and sinusoidal. The computational simulations are performed using the Matlab® and the Simulink. The results of simulations show that the proposed control increases the vehicle security and improves the drive ability by reducing the vertical wheel displacement and the workspace to be used by the damper when compared to the passive system. It also helps with the comfort of passengers, reducing the bodywork oscillations, maintaining levels of accelerating below considered uncomfortable by standard BS 6841, 1987. To verify the behavior of the proposed control, in the face of uncertainty, computational simulations are carried out, considering the possibility of parametric errors. The simulations, show that the Optimal Control, even when subject to uncertainties, remains stable and optimal.