986 resultados para Advanced control
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Tämän työn tarkoituksena oli löytää keinoja erään leijukerroskattilan typenoksidipäästöjen vähentämiseksi. Koska päästöt olivat jo alunperin alhaiset leijukerrostekniikan ja hybridin SNCR/SCR –typenpoistolaitteiston ansiosta, päätettiin päästöjä lähteä vähentämään parantamalla ammoniakkiruiskutuksen säätöä. Alkuperäinen ammoniakkiruiskutuksen säätö oli liian hidas, jotta satunnaisten häiriöiden aiheuttamat typenoksidipiikit olisi pystytty poistamaan. Ammoniakkiruiskutusta parannettiin lisäämällä jokaiseen ammoniakkilinjaan mäntäpumput, joiden avulla ammoniakkia voidaan syöttää sinne, missä sitä eniten tarvitaan. Ammoniakkiruiskutuksen säätöön kehitettiin uusi sumeaan logiikkaan perustuva säätäjä. Myös muita kehittyneitä säätömenetelmiä kuten neuroverkkoa hyödynnettiin säätäjän kehityksessä. Ammoniakkiruiskutuksen säätäjää testattiin menestyksekkäästi Ruotsissa Brista Kraftin Märstassa sijaitsevalla voimalaitoksella
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The bandwidth achievable by using voltage mode control or current mode control in switch-mode power supply is limited by the switching frequency. Fast transient response requires high switching frequency, although lower switching frequencies could be more suitable for higher efficiency. This paper proposes the use of hysteretic control of the output capacitor $(C_{out})$ current to improve the dynamic response of the buck converter. An external voltage loop is required to accurately regulate the output voltage. The design of the hysteretic loop and the voltage loop are presented. Besides, it is presented a non-invasive current sensor that allows measuring the current in the capacitor. This strategy has been applied for DVS (dynamic voltage scaling) on a 5 MHz buck converter. Experimental results validate the proposed control technique and show fast transient response from 1.5 V to 2.5 V in 2 $mu{rm s}$.
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Nowadays robots have made their way into real applications that were prohibitive and unthinkable thirty years ago. This is mainly due to the increase in power computations and the evolution in the theoretical field of robotics and control. Even though there is plenty of information in the current literature on this topics, it is not easy to find clear concepts of how to proceed in order to design and implement a controller for a robot. In general, the design of a controller requires of a complete understanding and knowledge of the system to be controlled. Therefore, for advanced control techniques the systems must be first identified. Once again this particular objective is cumbersome and is never straight forward requiring of great expertise and some criteria must be adopted. On the other hand, the particular problem of designing a controller is even more complex when dealing with Parallel Manipulators (PM), since their closed-loop structures give rise to a highly nonlinear system. Under this basis the current work is developed, which intends to resume and gather all the concepts and experiences involve for the control of an Hydraulic Parallel Manipulator. The main objective of this thesis is to provide a guide remarking all the steps involve in the designing of advanced control technique for PMs. The analysis of the PM under study is minced up to the core of the mechanism: the hydraulic actuators. The actuators are modeled and experimental identified. Additionally, some consideration regarding traditional PID controllers are presented and an adaptive controller is finally implemented. From a macro perspective the kinematic and dynamic model of the PM are presented. Based on the model of the system and extending the adaptive controller of the actuator, a control strategy for the PM is developed and its performance is analyzed with simulation.
Resumo:
Automation of managed pressure drilling (MPD) enhances the safety and increases efficiency of drilling and that drives the development of controllers and observers for MPD. The objective is to maintain the bottom hole pressure (BHP) within the pressure window formed by the reservoir pressure and fracture pressure and also to reject kicks. Practical MPD automation solutions must address the nonlinearities and uncertainties caused by the variations in mud flow rate, choke opening, friction factor, mud density, etc. It is also desired that if pressure constraints are violated the controller must take appropriate actions to reject the ensuing kick. The objectives are addressed by developing two controllers: a gain switching robust controller and a nonlinear model predictive controller (NMPC). The robust gain switching controller is designed using H1 loop shaping technique, which was implemented using high gain bumpless transfer and 2D look up table. Six candidate controllers were designed in such a way they preserve robustness and performance for different choke openings and flow rates. It is demonstrated that uniform performance is maintained under different operating conditions and the controllers are able to reject kicks using pressure control and maintain BHP during drill pipe extension. The NMPC was designed to regulate the BHP and contain the outlet flow rate within certain tunable threshold. The important feature of that controller is that it can reject kicks without requiring any switching and thus there is no scope for shattering due to switching between pressure and flow control. That is achieved by exploiting the constraint handling capability of NMPC. Active set method was used for computing control inputs. It is demonstrated that NMPC is able to contain kicks and maintain BHP during drill pipe extension.
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En este proyecto se ha desarrollado estrategias de control avanzadas para plantas de depuración de aguas residuales urbanas que eliminan conjuntamente materia orgánica, nitrógeno y fósforo. Las estrategias se han basado en el estudio multivariable del comportamiento del sistema, que ha producido subsidios para la utilización de lazos de control feedforward, de control predictivo y de un control de costes que automáticamente enviaba las consignas más adecuadas para los controladores de proceso. Para el desarrollo de las estrategias, se ha creado un sistema virtual de simulación (simulador) de plantas de depuradoras, basado en datos de literatura. Para el caso de una planta real, se ha desarrollado un simulador de la planta de Manresa (Catalunya). Sin embargo, el sistema de Manresa se ha utilizado exclusivamente para auxiliar los ingenieros de la planta en la tomada de decisiones de cambio de configuración para que la eliminación de fósforo se dé por la ruta biológica y no por la ruta química. La implementación de los simuladores ha permitido hacer muchas pruebas que en una planta real demandarían mucho tiempo y consumirían muchos recursos energéticos y financieros. Las estrategias de control más elaboradas han podido ahorrar hasta 150.000,00 Euros por año en relación a la operación de la planta sin el control automático. Cuanto a los estudios del modelo de la planta real, se concluyó que la eliminación biológica de fósforo puede sustituir el actual proceso químico de eliminación de fósforo, bajando los costes operacionales (costes del agente precipitante).
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This paper presents a multiprotocol mobile application for building automation which supports and enables the integration of the most representative control technologies such as KNX, LonWorks and X-10. The application includes a real-time monitoring service. Finally, advanced control functionalities based on gestures recognition and predefined scenes have been implemented. This application has been developed and tested in the Energy Efficiency Research Facility located at CeDInt-UPM, where electrical loads, blinds and HVAC and lighting systems can be controlled.
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This paper addresses advanced control of a biological nutrient removal (BNR) activated sludge process. Based on a previously validated distributed parameter model of the BNR activated sludge process, we present robust multivariable controller designs for the process, involving loop shaping of plant model, robust stability and performance analyses. Results from three design case studies showed that a multivariable controller with stability margins of 0.163, 0.492 and 1.062 measured by the normalised coprime factor, multiplicative and additive uncertainties respectively give the best results for meeting performance robustness specifications. The controller robustly stabilises effluent nutrients in the presence of uncertainties with the behaviour of phosphorus accumulating organisms as well as to effectively attenuate major disturbances introduced as step changes. This study also shows that, performance of the multivariable robust controller is superior to multi-loops SISO PI controllers for regulating the BNR activated sludge process in terms of robust stability and performance and controlling the process using inlet feed flowrate is infeasible. (C) 2003 Elsevier Ltd. All rights reserved.
Resumo:
The objective of the PhD thesis was to research technologies and strategies to reduce fuel consumption and pollutants emission produced by internal combustion engines. In order to meet this objective my activity was focused on the research of advanced controls based on cylinder pressure feedback. These types of control strategies were studied because they present promising results in terms of engine efficiency enhancement. In the PhD dissertation two study cases are presented. The first case is relative to a control strategy to be used at the test bench for the optimisation of the spark advance calibration of motorcycle Engine. The second case is relative to a control strategy to be used directly on board of mining engines with the objective or reducing the engine consumption and correct ageing effects. In both cases the strategies proved to be effective but their implementation required the use of specific toolchains for the measure of the cylinder pressure feedback that for a matter of cost makes feasible the strategy use only for applications: • At test bench • In small-markets like large off-road engines The major bottleneck that prevents the implementation of these strategies on mass production is the cost of cylinder pressure sensor. In order to tackle this issue, during the PhD research, the development of a low-cost sensor for the estimation of cylinder pressure was studied. The prototype was a piezo-electric washer designed to replace the standard spark-plug washer or high-pressure fuel injectors gasket. From the data analysis emerged the possibility to use the piezo-electric prototype signal to evaluate with accuracy several combustion metrics compatible for the implementation of advanced control strategies in on-board applications. Overall, the research shows that advanced combustion controls are feasible and beneficial, not only at the test bench or on stationary engines, but also in mass-produced engines.
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In pursuit of aligning with the European Union's ambitious target of achieving a carbon-neutral economy by 2050, researchers, vehicle manufacturers, and original equipment manufacturers have been at the forefront of exploring cutting-edge technologies for internal combustion engines. The introduction of these technologies has significantly increased the effort required to calibrate the models implemented in the engine control units. Consequently the development of tools that reduce costs and the time required during the experimental phases, has become imperative. Additionally, to comply with ever-stricter limits on 〖"CO" 〗_"2" emissions, it is crucial to develop advanced control systems that enhance traditional engine management systems in order to reduce fuel consumption. Furthermore, the introduction of new homologation cycles, such as the real driving emissions cycle, compels manufacturers to bridge the gap between engine operation in laboratory tests and real-world conditions. Within this context, this thesis showcases the performance and cost benefits achievable through the implementation of an auto-adaptive closed-loop control system, leveraging in-cylinder pressure sensors in a heavy-duty diesel engine designed for mining applications. Additionally, the thesis explores the promising prospect of real-time self-adaptive machine learning models, particularly neural networks, to develop an automatic system, using in-cylinder pressure sensors for the precise calibration of the target combustion phase and optimal spark advance in a spark-ignition engines. To facilitate the application of these combustion process feedback-based algorithms in production applications, the thesis discusses the results obtained from the development of a cost-effective sensor for indirect cylinder pressure measurement. Finally, to ensure the quality control of the proposed affordable sensor, the thesis provides a comprehensive account of the design and validation process for a piezoelectric washer test system.
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In this thesis, the problem of controlling a quadrotor UAV is considered. It is done by presenting an original control system, designed as a combination of Neural Networks and Disturbance Observer, using a composite learning approach for a system of the second order, which is a novel methodology in literature. After a brief introduction about the quadrotors, the concepts needed to understand the controller are presented, such as the main notions of advanced control, the basic structure and design of a Neural Network, the modeling of a quadrotor and its dynamics. The full simulator, developed on the MATLAB Simulink environment, used throughout the whole thesis, is also shown. For the guidance and control purposes, a Sliding Mode Controller, used as a reference, it is firstly introduced, and its theory and implementation on the simulator are illustrated. Finally the original controller is introduced, through its novel formulation, and implementation on the model. The effectiveness and robustness of the two controllers are then proven by extensive simulations in all different conditions of external disturbance and faults.
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With the development of new technologies, Air Traffic Control, in the nearby of the airport, switched from a purely visual control to the use of radar, sensors and so on. As the industry is switching to the so-called Industry 4.0, also in this frame, it would be possible to implement some of the new tools that can facilitate the work of Air Traffic Controllers. The European Union proposed an innovative project to help the digitalization of the European Sky by means of the Single European Sky ATM Research (SESAR) program, which is the foundation on which the Single European Sky (SES) is based, in order to improve the already existing technologies to transform Air Traffic Management in Europe. Within this frame, the Resilient Synthetic Vision for Advanced Control Tower Air Navigation Service Provision (RETINA) project, which saw the light in 2016, studied the possibility to apply new tools within the conventional control tower to reduce the air traffic controller workload, thanks to the improvements in the augmented reality technologies. After the validation of RETINA, the Digital Technologies for Tower (DTT) project was established and the solution proposed by the University of Bologna aimed, among other things, to introduce Safety Nets in a Head-Up visualization. The aim of this thesis is to analyze the Safety Nets in use within the control tower and, by developing a working concept, implement them in a Head-Up view to be tested by Air Traffic Control Operators (ATCOs). The results, coming from the technical test, show that this concept is working and it could be leading to a future implementation in a real environment, as it improves the air traffic controller working conditions also when low visibility conditions apply.
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The design and development of the swordfish autonomous surface vehicle (ASV) system is discussed. Swordfish is an ocean capable 4.5 m long catamaran designed for network centric operations (with ocean and air going vehicles and human operators). In the basic configuration, Swordfish is both a survey vehicle and a communications node with gateways for broadband, Wi-Fi and GSM transports and underwater acoustic modems. In another configuration, Swordfish mounts a docking station for the autonomous underwater vehicle Isurus from Porto University. Swordfish has an advanced control architecture for multi-vehicle operations with mixed initiative interactions (human operators are allowed to interact with the control loops).