362 research outputs found

    Optimization and multivariable control of refrigeration systems

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    Los ciclos de refrigeración por compresión de vapor constituyen el método más extendido a nivel mundial para la generación de frío. Estos sistemas se utilizan en áreas tan diversas como regulación de la temperatura en estancias habitadas, almacenamiento y transporte de alimentos y múltiples procesos industriales. Dado el considerable impacto causado por el consumo energético de estos sistemas en los balances económicos y medioambientales de los países desarrollados y en vías de desarrollo, y teniendo en cuenta la escasez creciente de fuentes de energía fósiles y el desarrollo todavía lento de las diferentes tecnologías de energía renovable, la operación óptima en términos de eficiencia energética de los sistemas de refrigeración por compresión de vapor existentes se presenta como un problema clave que abordar. Esta Tesis aborda la operación óptima de los ciclos de refrigeración desde el punto de vista de la eficiencia energética. Aunque el trabajo se centra principalmente en sistemas de una etapa de compresión y un recinto a refrigerar, se analizan también otras configuraciones con varias etapas y varios recintos. Existen varios factores clave para alcanzar la operación óptima de un sistema de refrigeración en el campo del Control Automático: el modelado, la optimización y el control propiamente dicho. En primer lugar, se estudia ampliamente el modelado estático y dinámico de los sistemas de refrigeración. En cuanto al segundo, se desarrolla un modelo dinámico simplificado y orientado al control de un ciclo de una etapa de compresión y un recinto a refrigerar. El objetivo es que pueda ser incorporado en estrategias de control basado en modelo, donde se requieren tanto una baja carga computacional como una descripción suficientemente precisa de la dinámica dominante del sistema, de acuerdo con los objetivos de control. En segundo lugar, se analiza la operación óptima en régimen permanente de un ciclo de una etapa de compresión y un recinto a refrigerar. Dada una cierta demanda de frío, el objetivo de la fase de optimización es calcular el ciclo en régimen permanente que alcanza la máxima eficiencia energética posible asegurando la satisfacción de la demanda de frío y a la vez respetando las restricciones de operación. Una vez calculado, se pretende que este ciclo óptimo constituya la referencia a seguir por parte del controlador. Finalmente, se estudia asimismo el problema de control. En la literatura sobre sistemas de refrigeración se encuentran principalmente dos esquemas: el control convencional y el control centrado en la eficiencia energética. En el primer esquema, además de la referencia impuesta por la demanda de frío, se impone un valor bajo pero constante como referencia para el grado de sobrecalentamiento del refrigerante a la salida del evaporador, to achieve the cycle defined by the optimization stage by manipulating the available control actions. Therefore, the controllability of the one-stage, one-load-demand cycle is analysed using linear theory and a nonlinear pointwise analysis based on the phase portrait method. Given the conclusions of the controllability analysis, a suboptimal hierarchical control strategy is proposed to achieve the highest possible efficiency while satisfying the cooling load. Most contributions of this Thesis are of theoretical nature. Notwithstanding, the application of the proposed control strategy to a multi-compression-stage, multi-loaddemand experimental plant is intended. Then, steady-state identification of the plant is performed from experimental data, whereas validation of the models considering different plant configurations is also carried out.Premio Extraordinario de Doctorado U

    Sensor failure detection system

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    Advanced concepts for detecting, isolating, and accommodating sensor failures were studied to determine their applicability to the gas turbine control problem. Five concepts were formulated based upon such techniques as Kalman filters and a screening process led to the selection of one advanced concept for further evaluation. The selected advanced concept uses a Kalman filter to generate residuals, a weighted sum square residuals technique to detect soft failures, likelihood ratio testing of a bank of Kalman filters for isolation, and reconfiguring of the normal mode Kalman filter by eliminating the failed input to accommodate the failure. The advanced concept was compared to a baseline parameter synthesis technique. The advanced concept was shown to be a viable concept for detecting, isolating, and accommodating sensor failures for the gas turbine applications

    Modelling and Control of Aircraft Gas Turbine Engines

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    In this thesis the main theme is to demonstrate the potential performance improvements of gas turbine engines that are brought about by using multivariable control systems. Particular emphasis is on designing such control systems using the well-established engine thermodynamic models since these models are considered as the true representations of engine thermodynamic process and enable engine variable geometry features to be easily incorporated and their effects studied

    Advanced and novel modeling techniques for simulation, optimization and monitoring chemical engineering tasks with refinery and petrochemical unit applications

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    Engineers predict, optimize, and monitor processes to improve safety and profitability. Models automate these tasks and determine precise solutions. This research studies and applies advanced and novel modeling techniques to automate and aid engineering decision-making. Advancements in computational ability have improved modeling software’s ability to mimic industrial problems. Simulations are increasingly used to explore new operating regimes and design new processes. In this work, we present a methodology for creating structured mathematical models, useful tips to simplify models, and a novel repair method to improve convergence by populating quality initial conditions for the simulation’s solver. A crude oil refinery application is presented including simulation, simplification tips, and the repair strategy implementation. A crude oil scheduling problem is also presented which can be integrated with production unit models. Recently, stochastic global optimization (SGO) has shown to have success of finding global optima to complex nonlinear processes. When performing SGO on simulations, model convergence can become an issue. The computational load can be decreased by 1) simplifying the model and 2) finding a synergy between the model solver repair strategy and optimization routine by using the initial conditions formulated as points to perturb the neighborhood being searched. Here, a simplifying technique to merging the crude oil scheduling problem and the vertically integrated online refinery production optimization is demonstrated. To optimize the refinery production a stochastic global optimization technique is employed. Process monitoring has been vastly enhanced through a data-driven modeling technique Principle Component Analysis. As opposed to first-principle models, which make assumptions about the structure of the model describing the process, data-driven techniques make no assumptions about the underlying relationships. Data-driven techniques search for a projection that displays data into a space easier to analyze. Feature extraction techniques, commonly dimensionality reduction techniques, have been explored fervidly to better capture nonlinear relationships. These techniques can extend data-driven modeling’s process-monitoring use to nonlinear processes. Here, we employ a novel nonlinear process-monitoring scheme, which utilizes Self-Organizing Maps. The novel techniques and implementation methodology are applied and implemented to a publically studied Tennessee Eastman Process and an industrial polymerization unit

    New Approaches in Automation and Robotics

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    The book New Approaches in Automation and Robotics offers in 22 chapters a collection of recent developments in automation, robotics as well as control theory. It is dedicated to researchers in science and industry, students, and practicing engineers, who wish to update and enhance their knowledge on modern methods and innovative applications. The authors and editor of this book wish to motivate people, especially under-graduate students, to get involved with the interesting field of robotics and mechatronics. We hope that the ideas and concepts presented in this book are useful for your own work and could contribute to problem solving in similar applications as well. It is clear, however, that the wide area of automation and robotics can only be highlighted at several spots but not completely covered by a single book

    Applications of Mathematical Models in Engineering

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    The most influential research topic in the twenty-first century seems to be mathematics, as it generates innovation in a wide range of research fields. It supports all engineering fields, but also areas such as medicine, healthcare, business, etc. Therefore, the intention of this Special Issue is to deal with mathematical works related to engineering and multidisciplinary problems. Modern developments in theoretical and applied science have widely depended our knowledge of the derivatives and integrals of the fractional order appearing in engineering practices. Therefore, one goal of this Special Issue is to focus on recent achievements and future challenges in the theory and applications of fractional calculus in engineering sciences. The special issue included some original research articles that address significant issues and contribute towards the development of new concepts, methodologies, applications, trends and knowledge in mathematics. Potential topics include, but are not limited to, the following: Fractional mathematical models; Computational methods for the fractional PDEs in engineering; New mathematical approaches, innovations and challenges in biotechnologies and biomedicine; Applied mathematics; Engineering research based on advanced mathematical tools

    International Symposium on Magnetic Suspension Technology, Part 1

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    The goal of the symposium was to examine the state of technology of all areas of magnetic suspension and to review related recent developments in sensors and controls approaches, superconducting magnet technology, and design/implementation practices. The symposium included 17 technical sessions in which 55 papers were presented. The technical session covered the areas of bearings, sensors and controls, microgravity and vibration isolation, superconductivity, manufacturing applications, wind tunnel magnetic suspension systems, magnetically levitated trains (MAGLEV), space applications, and large gap magnetic suspension systems

    Hybrid Integrator-Gain Systems:Analysis, Design, and Applications

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    Technology for large space systems: A bibliography with indexes (supplement 14)

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    This bibliography lists 645 reports, articles and other documents introduced into the NASA scientific and technical information system between July 1, 1985 and December 31, 1985. Its purpose is to provide helpful information to the researcher, manager, and designer in technology development and mission design according to system, interactive analysis and design, structural and thermal analysis and design, structural concepts and control systems, electronics, advanced materials, assembly concepts, propulsion, and solar power satellite systems

    Process analytical technology in food biotechnology

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    Biotechnology is an area where precision and reproducibility are vital. This is due to the fact that products are often in form of food, pharmaceutical or cosmetic products and therefore very close to the human being. To avoid human error during the production or the evaluation of the quality of a product and to increase the optimal utilization of raw materials, a very high amount of automation is desired. Tools in the food and chemical industry that aim to reach this degree of higher automation are summarized in an initiative called Process Analytical Technology (PAT). Within the scope of the PAT, is to provide new measurement technologies for the purpose of closed loop control in biotechnological processes. These processes are the most demanding processes in regards of control issues due to their very often biological rate-determining component. Most important for an automation attempt is deep process knowledge, which can only be achieved via appropriate measurements. These measurements can either be carried out directly, measuring a crucial physical value, or if not accessible either due to the lack of technology or a complicated sample state, via a soft-sensor.Even after several years the ideal aim of the PAT initiative is not fully implemented in the industry and in many production processes. On the one hand a lot effort still needs to be put into the development of more general algorithms which are more easy to implement and especially more reliable. On the other hand, not all the available advances in this field are employed yet. The potential users seem to stick to approved methods and show certain reservations towards new technologies.Die Biotechnologie ist ein Wissenschaftsbereich, in dem hohe Genauigkeit und Wiederholbarkeit eine wichtige Rolle spielen. Dies ist der Tatsache geschuldet, dass die hergestellten Produkte sehr oft den Bereichen Nahrungsmitteln, Pharmazeutika oder Kosmetik angehöhren und daher besonders den Menschen beeinflussen. Um den menschlichen Fehler bei der Produktion zu vermeiden, die Qualität eines Produktes zu sichern und die optimale Verwertung der Rohmaterialen zu gewährleisten, wird ein besonders hohes Maß an Automation angestrebt. Die Werkzeuge, die in der Nahrungsmittel- und chemischen Industrie hierfür zum Einsatz kommen, werden in der Process Analytical Technology (PAT) Initiative zusammengefasst. Ziel der PAT ist die Entwicklung zuverlässiger neuer Methoden, um Prozesse zu beschreiben und eine automatische Regelungsstrategie zu realisieren. Biotechnologische Prozesse gehören hierbei zu den aufwändigsten Regelungsaufgaben, da in den meisten Fällen eine biologische Komponente der entscheidende Faktor ist. Entscheidend für eine erfolgreiche Regelungsstrategie ist ein hohes Maß an Prozessverständnis. Dieses kann entweder durch eine direkte Messung der entscheidenden physikalischen, chemischen oder biologischen Größen gewonnen werden oder durch einen SoftSensor. Zusammengefasst zeigt sich, dass das finale Ziel der PAT Initiative auch nach einigen Jahren des Propagierens weder komplett in der Industrie noch bei vielen Produktionsprozessen angekommen ist. Auf der einen Seite liegt dies mit Sicherheit an der Tatsache, dass noch viel Arbeit in die Generalisierung von Algorithmen gesteckt werden muss. Diese müsse einfacher zu implementieren und vor allem noch zuverlässiger in der Funktionsweise sein. Auf der anderen Seite wurden jedoch auch Algorithmen, Regelungsstrategien und eigne Ansätze für einen neuartigen Sensor sowie einen Soft-Sensors vorgestellt, die großes Potential zeigen. Nicht zuletzt müssen die möglichen Anwender neue Strategien einsetzen und Vorbehalte gegenüber unbekannten Technologien ablegen
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