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No description available.

Thesis--Auburn University, 2009. / Abstract. Vita. Includes MatLab code. Includes bibliography (p.43-44).

The attitude determination and control subsystem (ADCS) is a critical part of any satellite conducting scientific experiments that require accurate positioning (such as Earth observation and solar spectroscopy). The engineering design process of this subsystem has a long heritage; yet, it is surrounded by several limitations due to the stringent physical constraints imposed on small satellites. These limitations (e.g., limited computational capabilities, power, and volume) require an improved approach for the purpose of attitude determination (AD) and control. Previous space missions relied mostly on the extended Kalman filter (EKF) to estimate the relative orientation of the spacecraft because it yields an optimal estimator under the assumption that the measurement and process models are white Gaussian processes. However, this filter suffers from several limitations such as a high computational cost. This thesis addresses all the limitations found in small satellites by introducing a computationally efficient algorithm for AD based on a fuzzy inference system with a gradient decent optimization technique to calculate and optimize the bounds of the membership functions. Also, an optimal controller based on a fractional proportional-integral-derivative controller has been implemented to provide an energy-efficient control scheme. The AD algorithm presented in this thesis relies on the residual information of the Earth magnetic field. In contrast to current approaches, the new algorithm is immune to several limitations such as sensitivity to initial conditions and divergence problems. Additionally, its computational cost has been reduced. Simulation results illustrate a higher pointing stability, while maintaining satisfying levels of pointing accuracy and increasing reliability. Moreover, the optimal controller designed provides a shorter time delay, settling time, and steady-state error. This demonstrates that accurate attitude determination and control can be conducted in small spacecraft.

Dissertation for the degree of Doctor of Science in Technology--Helsinki University of Technology, Espoo, 2002. / "ISSN 0781-5816." Includes bibliographical references (p. 65-71). Available online as a PDF file via the World Wide Web.

The purpose of this research work is to propose an improved method for real-time sensitivity analysis (SA) applicable to large-scale complex systems. Borrowed from the EventTracker principle of the interrelation of causal events, it deploys the Rank Order Clustering (ROC) method to automatically group every relevant system input to parameters that represent the system state (i.e. output). The fundamental principle of event modelling is that the state of a given system is a function of every acquirable piece of knowledge or data (input) of events that occur within the system and its wider operational environment unless proven otherwise. It therefore strives to build the theoretical and practical foundation for the engineering of input data. The event modelling platform proposed attempts to filter unwanted data, and more importantly, include information that was thought to be irrelevant at the outset of the design process. The underpinning logic of the proposed Event Clustering technique (EventiC) is to build causal relationship between the events that trigger the inputs and outputs of the system. EventiC groups inputs with relevant corresponding outputs and measures the impact of each input variable on the output variables in short spans of time (relative real-time). It is believed that this grouping of relevant input-output event data by order of its importance in real-time is the key contribution to knowledge in this subject area. Our motivation is that components of current complex and organised systems are capable of generating and sharing information within their network of interrelated devices and systems. In addition to being an intelligent recorder of events, EventiC could also be a platform for preliminary data and knowledge construction. This improvement in the quality, and at times the quantity of input data, may lead to improved higher level mathematical formalism. It is hoped that better models will translate into superior controls and decision making. It is therefore believed that the projected outcome of this research work can be used to predict, stabilize (control), and optimize (operational research) the work of complex systems in the shortest possible time. For proof of concept, EventiC was designed using the MATLAB package and implemented using real-time data from the monitoring and control system of a typical cement manufacturing plant. The purpose for this deployment was to test and validate the concept, and to demonstrate whether the clusters of input data and their levels of importance against system performance indicators could be approved by industry experts. EventiC was used as an input variable selection tool for improving the existing fuzzy controller of the plant. Finally, EventiC was compared with its predecessor EventTracker using the same case study. The results revealed improvements in both computational efficiency and the quality of input variable selection.

Made available in DSpace on 2014-12-17T14:08:37Z (GMT). No. of bitstreams: 1 Geraldo de Moura Lacerda_DISSERT.PDF: 1911121 bytes, checksum: 19c68900a038404a86d6d95ce757a46b (MD5) Previous issue date: 2009-12-09 / This work presents a proposal to detect interface in atmospheric oil tanks by installing a differential pressure level transmitter to infer the oil-water interface. The main goal of this project is to maximize the quantity of free water that is delivered to the drainage line by controlling the interface. A Fuzzy Controller has been implemented by using the interface transmitter as the Process Variable. Two ladder routine was generated to perform the control. One routine was developed to calculate the error and error variation. The other was generate to develop the fuzzy controller itself. By using rules, the fuzzy controller uses these variables to set the output. The output is the position variation of the drainage valve. Although the ladder routine was implemented into an Allen Bradley PLC, Control Logix family it can be implemented into any brand of PLCs / Este trabalho apresenta uma proposta para instala??o de um transmissor de n?vel por press?o diferencial que ser? usado para detec??o de interface em tanques de Petr?leo instalados pela Petrobras no estado do Rio Grande do Norte. Este transmissor medir? a vari?vel controlada n?vel, que ser? usada como entrada para um controlador fuzzy implementado em rotina ladder em um CLP Contrologix da Rockwell Automation. Este controlador comandar? a abertura ou fechamento das v?lvulas de sa?da de ?leo nos tanques, com o intuito de garantir a m?xima sa?da de ?gua no fundo do tanque sem a presen?a de ?leo. Apesar se existirem v?rias tecnologias para detec??o da interface, conforme ser? mostrado adiante, o controle da interface ? feito de forma manual, ou seja, por interm?dio do operador atrav?s de retiradas de amostras dos fluidos nos tanques em v?lvulas conhecidas como v?lvulas de retirada de amostras (tamb?m conhecidas como try cocks). O grande entrave ao uso das tecnologias existentes ? a complexidade do processo de tratamento, as varia??es na carga do petr?leo recebido, exist?ncia de sulfetos de ferro, etc. Neste trabalho, ? apresentada uma breve teoria sobre emuls?es, sobre os processos de separa??o de petr?leo e das v?rias tecnologias de detec??o de interface dispon?veis no mercado. Em seguida, a teoria de sistemas fuzzy ? comentada, bem como o projeto Detec??o de Interface baseado na medi??o de n?vel e uso de controladores fuzzy, objeto deste estudo, para fins de obten??o do t?tulo de Mestre em Engenharia de Petr?leo

Made available in DSpace on 2014-12-17T14:08:47Z (GMT). No. of bitstreams: 1 TiagoSB_DISSERT.pdf: 2511631 bytes, checksum: 6bc0111c2afb2c48acf040134ddb6f46 (MD5) Previous issue date: 2011-07-22 / From their early days, Electrical Submergible Pumping (ESP) units have excelled in lifting much greater liquid rates than most of the other types of artificial lift and developed by good performance in wells with high BSW, in onshore and offshore environments. For all artificial lift system, the lifetime and frequency of interventions are of paramount importance, given the high costs of rigs and equipment, plus the losses coming from a halt in production. In search of a better life of the system comes the need to work with the same efficiency and security within the limits of their equipment, this implies the need for periodic adjustments, monitoring and control. How is increasing the prospect of minimizing direct human actions, these adjustments should be made increasingly via automation. The automated system not only provides a longer life, but also greater control over the production of the well. The controller is the brain of most automation systems, it is inserted the logic and strategies in the work process in order to get you to work efficiently. So great is the importance of controlling for any automation system is expected that, with better understanding of ESP system and the development of research, many controllers will be proposed for this method of artificial lift. Once a controller is proposed, it must be tested and validated before they take it as efficient and functional. The use of a producing well or a test well could favor the completion of testing, but with the serious risk that flaws in the design of the controller were to cause damage to oil well equipment, many of them expensive. Given this reality, the main objective of the present work is to present an environment for evaluation of fuzzy controllers for wells equipped with ESP system, using a computer simulator representing a virtual oil well, a software design fuzzy controllers and a PLC. The use of the proposed environment will enable a reduction in time required for testing and adjustments to the controller and evaluated a rapid diagnosis of their efficiency and effectiveness. The control algorithms are implemented in both high-level language, through the controller design software, such as specific language for programming PLCs, Ladder Diagram language. / Desde a sua concep??o, as unidades de Bombeio Centr?fugo Submerso (BCS) destacaram- se pelas altas vaz?es desenvolvidas e pelo bom desempenho em po?os com alto BSW, tanto em ambientes onshore como offshore. Em qualquer sistema de eleva??o, sua vida ?til e a frequ?ncia das interven??es s?o de fundamental import?ncia, em virtude dos elevados custos das sondas e dos equipamentos, al?m dos prejuizos oriundos de uma parada na produ??o. Na busca por uma maior vida ?til do sistema, surge a necessidade de que o mesmo trabalhe com efici?ncia e dentro dos limites de seguran?a de seus equipamentos, isso implica na necessidade de peri?dicos ajustes, monitoramento e controle. Como ? crescente a perspectiva de se minimizar as a??es humanas diretas, esses ajustes dever?o ser feitos cada vez mais via automa??o. A automa??o do sistema n?o s? possibilita uma maior vida ?til, mas tamb?m um maior controle sobre a produ??o do po?o. O controlador ? o c?rebro da maioria dos sistemas de automa??o, concentrando l?gica e estrat?gias necess?rias a atua??o no processo de maneira a lev?-lo a trabalhar com efici?ncia. Tal ? a import?ncia do controle para qualquer sistema de automa??o que se espera que, com o desenvolver das pesquisas e melhor conhecimento do BCS, muitos controladores venham a ser propostos para este m?todo de eleva??o. Depois que um controlador ? proposto, o mesmo deve ser testado e validado antes de se tom?-lo como eficiente e funcional. O uso de um po?o produtor ou de um po?o de teste poderia viabilizar a realiza??o de testes, mas com o s?rio risco de que falhas no projeto do controlador viessem a ocasionar danos aos equipamentos do po?o, muitos deles de custo elevado. Diante dessa realidade, o objetivo deste trabalho ? apresentar um ambiente para avalia??o de controladores fuzzy para po?os equipados com o m?todo BCS, utilizando-se de um simulador computacional representando um po?o virtual, de um software de projeto de controladores fuzzy e de um CLP comercial. O uso do ambiente proposto possibilitar? uma redu??o no tempo requerido para a realiza??o dos testes e ajustes necess?rios ao controlador avaliado e um diagn?stico r?pido de sua efici?ncia e efic?cia. Os algoritmos de controle s?o implementados tanto em linguagem de alto n?vel, atrav?s do software de projeto de controladores, como em linguagem espec?fica para programa??o de CLPs, a linguagem de Diagramas Ladder.