Fonte de carga de condensadores de alta tensão com compensação de fator potência

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Sintonia de controladores baseada em Sistemas de Inferência Difusa

Este trabalho de pesquisa e desenvolvimento tem como fundamento principal o Conceito de Controlo por Lógica Difusa. Utilizando as ferramentas do software Matlab, foi possível desenvolver um controlador com base na inferência difusa que permitisse controlar qualquer tipo de sistema físico real, independentemente das suas características. O Controlo Lógico Difuso, do inglês “Fuzzy Control”, é um tipo de controlo muito particular, pois permite o uso simultâneo de dados numéricos com variáveis linguísticas que tem por base o conhecimento heurístico dos sistemas a controlar. Desta forma, consegue-se quantificar, por exemplo, se um copo está “meio cheio” ou “meio vazio”, se uma pessoa é “alta” ou “baixa”, se está “frio” ou “muito frio”. O controlo PID é, sem dúvida alguma, o controlador mais amplamente utilizado no controlo de sistemas. Devido à sua simplicidade de construção, aos reduzidos custos de aplicação e manutenção e aos resultados que se obtêm, este controlador torna-se a primeira opção quando se pretende implementar uma malha de controlo num determinado sistema. Caracterizado por três parâmetros de ajuste, a saber componente proporcional, integral e derivativa, as três em conjunto permitem uma sintonia eficaz de qualquer tipo de sistema. De forma a automatizar o processo de sintonia de controladores e, aproveitando o que melhor oferece o Controlo Difuso e o Controlo PID, agrupou-se os dois controladores, onde em conjunto, como poderemos constatar mais adiante, foram obtidos resultados que vão de encontro com os objectivos traçados. Com o auxílio do simulink do Matlab, foi desenvolvido o diagrama de blocos do sistema de controlo, onde o controlador difuso tem a tarefa de supervisionar a resposta do controlador PID, corrigindo-a ao longo do tempo de simulação. O controlador desenvolvido é denominado por Controlador FuzzyPID. Durante o desenvolvimento prático do trabalho, foi simulada a resposta de diversos sistemas à entrada em degrau unitário. Os sistemas estudados são na sua maioria sistemas físicos reais, que representam sistemas mecânicos, térmicos, pneumáticos, eléctricos, etc., e que podem ser facilmente descritos por funções de transferência de primeira, segunda e de ordem superior, com e sem atraso.

Controladores linguísticos Fuzzy

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Jatkuvatoimisen sellukeittimen säätöjen suorituskyvyn analysointi

Työssä tarkastellaan yleisiä menetelmiä säätöpiirien suorituskyvyn analysointiin ja sovelletaan niitä jatkuvatoimisen sellukeittimen säätöihin. Esitellyt menetelmät tarjoavat keinoja myös huonon säätötuloksen syyn selvittämiseen ja vinkkejä paremman suorituskyvyn saavuttamiseksi. Analyysissä edettiin top-down periaatteen mukaisesti lähtien liikkeelle keittimen tärkeimmästä säädöstä eli kappaluvun säädöstä. Sitten etsittiin tähän vaikuttavia tekijöitä mitatuista suureista. Seuraavaksi arvioitiin tärkeimmäksi katsotun tekijän (hakepinnankorkeus) säädön suorituskyky, jossa havaittiin parannettavaa. Lopuksi hakepinnankorkeuden säädön viritystämuutettiin ja tehtiin identifiointikoe säätörakenteen uudelleen järjestelyä varten.

SIMULATION OF AMB SUPPORTED ROTOR DURING DROP ON RETAINER BEARINGS

The active magnetic bearings present a new technology which has many advantages compared to traditional bearing designs. Active magnetic bearings, however, require retainer bearings order to prevent damages in the event of a component, power or a control loop failure. In the dropdown situation, when the rotor drops from the magnetic bearings to the retainer bearings, the design parameters of the retainer bearings have a significant influence on the behaviour of the rotor. In this study, the dynamics of an active magnetic bearings supported electric motor during rotor drop on retainer bearings is studied using a multibody simulation approach. Various design parameters of retainer bearings are studied using a simulation model while results are compared with those found in literature. The retainer bearings are modelled using a detailed ball bearing model, which accounts damping and stiffness properties, oil film and friction between races and rolling elements. The model of the ball bearings includes inertia description of rollingelements. The model of the magnetic bearing system contains unbalances of the rotor and stiffness and damping properties of support. In this study, a computationally efficient contact model between the rotor and the retainer bearings is proposed. In addition, this work introduces information for the design of physicalprototype and its retainer bearings.

Paperikoneen laatusäätöjärjestelmän uusinnan vaikutukset laatusäätöjen suorituskykyyn

Tutkimuksen kohteena olleen UPM-Kymmene Oyj Kajaanin tehtaan PK3:n laatusäätöjärjestelmä ja mittapalkki uusittiin, jolloin haluttiin selvittää uusinnan vaikutuksia laatusäätöjen suorituskykyyn ja paperin laatuun. Työn kirjallisessa osassa perehdyttiin paperinvalmistusprosessin osiin kyseisen sanomalehtipaperikoneen tapauksessa sekä keskeisimpiin paperin laatuominaisuuksiin liittyviin mittaus- ja säätölaitteisiin sekä niiden toimintaan. Seurattaviksi paperin laatusuureiksi valittiin neliömassa, kuivamassa, kosteus ja paksuus, jotka ovat sanomalehtipaperin tärkeimpiä online-mitattavia ominaisuuksia. Paperin laatusuureiden seurantaan käytetään erilaisia tunnuslukuja ja työkaluja, joita on esitelty tässä työssä. Laatusuureiden konesuuntaisen ja poikkisuuntaisen seurannan tunnusluvuksi valittiin yleisesti käytössä oleva 2σ-keskiarvohajonta. Säätöjen suorituskykyä seurattiin suorituskykykolmion ohjausmatkaindeksien (CTI) ja erosuureen integraalien (IAE) avulla. Kokeellisessa osassa kerättiin mittaustietoja sekä vanhan että uuden laatusäätöjärjestelmän aikana. Seurattavat ajotilanteet paperikoneella jaettiin stabiiliin ajoon ja muutostilanteisiin, jotka käsittävät katkot ja lajinvaihtotilanteet. Stabiilin ajon aikana selvitettiin laatusuureiden hajontojen ja säätöjen suorituskykyindeksien normaaleissa tasoissa tapahtuneet muutokset. Muutostilanteiden osalta haluttiin selvittää, nopeuttaako järjestelmäuusinta katkoista toipumista ja lajinvaihtoaikaa. Stabiilin ajon seurannasta saatujen tulosten perusteella neliömassan ja kuivamassan konesuuntaiset hajonnat kasvoivat järjestelmäuusinnan myötä, mutta kosteuden konesuuntaiset hajonnat pienenivät. Laatusuureiden poikkisuuntaisista hajonnoista neliömassan sekä kuivamassan hajonnat kasvoivat ja kosteuden sekä paksuuden hajonnat pienenivät joidenkin lajien osalta. Poikkisuuntaisten laatusuureiden, etenkin paksuuden, toipuminen katkon jälkeen nopeutui. Myös lajinvaihtoon kuluva aika lyheni poikkisuuntaisilla laatusuureilla. Muutostilanteiden konesuuntaisten hajontojen asettumisajat eivät juuri parantuneet.

Toimitusketjun mallinnuksen tarpeet ja rakenne LOCOMOTIVE projekstissa

Työn tavoitteena oli kuvata ja priorisoida toimitusketjun dynaamisen mallinnustyökalun vaatimukset, sekä muodostaa tämän pohjalta ohjelmistokehitystä tukeva oliomalli. Vaatimuksia selvitettiin teoreettisen tarkastelun, aiemmin toteutettujen kyselytutkimusten sekä viiden pilottitapauksen avulla. Toimitusketjun hallinta ei ole pelkästään materiaalivirtojen vaan myös näihin liittyvän informaation hallintaa. Holististen toimitusketjuongelmien mallintaminen edellyttää siis informaatiovirtojen ja niitä saatelevien ohjausmekanisemien mallintamista. Markkinoilla on selkeästi tilaa tukijärjestelmille, jotka mahdollistaisivat multidimensionaalisten - tuotto, aika, palvelu - toimitusketjuongelmien tarkastelun. Systeemidynamiikan teorian mukaisesti oliomallin lähtökohdaksi valittiin tärkeimpien takaisinkytkentäsilmukkojen mallinnus. Takaisinkytkentäsilmukoiden avulla kyetään mallintamaan kompleksisia systeemejä ajan suhteen. Mallinnetut toimitusketjujen takaisinkytkentäsilmukkat ovat operaatio-, ohjaus-, kysyntä- ja strategiasilmukka. Toimitusketjun ohjausmekanismien, sekä systeemidynamiikan perusteiden pohjalta mallinnustyökalun vaatimuksista muodostettiin oliomalli. Muodostettu oliomalli on Locomotiven - toimitusketjun mallinnustyökalun - perusta.

A Test Bed Applied Mobile Robot Navigation

It is presented a test bed applied to studies on dynamics, control, and navigation of mobile robots. A cargo ship scale model was chosen, which can be radio-controlled or operated autonomously through an embedded control system. A control program, which manages on board mission execution, is implemented on a microcontroller. Navigation is based on an electronic compass, which includes automatic compensation for pitch and roll motions. Heading control loop is based on this sensor, and on a rudder positioning system. A propulsion control system is also implemented. Typical manoeuvres as the turning test and "zig-zag", were implemented and tested. They are included on a manoeuvre library, and can be accessed independently or in combined modes. The embedded system is also in charge of signal acquisition and storing during the missions. It is possible to analyse experiments on identification of ship dynamics, control, and navigation, through the data transferred to a PC by serial communication. Navigation is going to be improved by including inertial sensors on board, and a DGPS. Preliminary tests are aimed to ship identification, and manoeuvrability, using free model tests. Future steps include extending this system for developing other mobile robots as, ROVs, AUVs, and aerial vehicles.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Neuartige Verfahren für die Überwachung und Diagnose von aktiv magnetgelagerten rotierenden Maschinen

Mit aktiven Magnetlagern ist es möglich, rotierende Körper durch magnetische Felder berührungsfrei zu lagern. Systembedingt sind bei aktiv magnetgelagerten Maschinen wesentliche Signale ohne zusätzlichen Aufwand an Messtechnik für Diagnoseaufgaben verfügbar. In der Arbeit wird ein Konzept entwickelt, das durch Verwendung der systeminhärenten Signale eine Diagnose magnetgelagerter rotierender Maschinen ermöglicht und somit neben einer kontinuierlichen Anlagenüberwachung eine schnelle Bewertung des Anlagenzustandes gestattet. Fehler können rechtzeitig und ursächlich in Art und Größe erkannt und entsprechende Gegenmaßnahmen eingeleitet werden. Anhand der erfassten Signale geschieht die Gewinnung von Merkmalen mit signal- und modellgestützten Verfahren. Für den Magnetlagerregelkreis erfolgen Untersuchungen zum Einsatz modellgestützter Parameteridentifikationsverfahren, deren Verwendbarkeit wird bei der Diagnose am Regler und Leistungsverstärker nachgewiesen. Unter Nutzung von Simulationsmodellen sowie durch Experimente an Versuchsständen werden die Merkmalsverläufe im normalen Referenzzustand und bei auftretenden Fehlern aufgenommen und die Ergebnisse in einer Wissensbasis abgelegt. Diese dient als Grundlage zur Festlegung von Grenzwerten und Regeln für die Überwachung des Systems und zur Erstellung wissensbasierter Diagnosemodelle. Bei der Überwachung werden die Merkmalsausprägungen auf das Überschreiten von Grenzwerten überprüft, Informationen über erkannte Fehler und Betriebszustände gebildet sowie gegebenenfalls Alarmmeldungen ausgegeben. Sich langsam anbahnende Fehler können durch die Berechnung der Merkmalstrends mit Hilfe der Regressionsanalyse erkannt werden. Über die bisher bei aktiven Magnetlagern übliche Überwachung von Grenzwerten hinaus erfolgt bei der Fehlerdiagnose eine Verknüpfung der extrahierten Merkmale zur Identifizierung und Lokalisierung auftretender Fehler. Die Diagnose geschieht mittels regelbasierter Fuzzy-Logik, dies gestattet die Einbeziehung von linguistischen Aussagen in Form von Expertenwissen sowie die Berücksichtigung von Unbestimmtheiten und ermöglicht damit eine Diagnose komplexer Systeme. Für Aktor-, Sensor- und Reglerfehler im Magnetlagerregelkreis sowie Fehler durch externe Kräfte und Unwuchten werden Diagnosemodelle erstellt und verifiziert. Es erfolgt der Nachweis, dass das entwickelte Diagnosekonzept mit beherrschbarem Rechenaufwand korrekte Diagnoseaussagen liefert. Durch Kaskadierung von Fuzzy-Logik-Modulen wird die Transparenz des Regelwerks gewahrt und die Abarbeitung der Regeln optimiert. Endresultat ist ein neuartiges hybrides Diagnosekonzept, welches signal- und modellgestützte Verfahren der Merkmalsgewinnung mit wissensbasierten Methoden der Fehlerdiagnose kombiniert. Das entwickelte Diagnosekonzept ist für die Anpassung an unterschiedliche Anforderungen und Anwendungen bei rotierenden Maschinen konzipiert.

Distributed fuzzy logic for building management systems using local operating networks

This paper describes the development of an experimental distributed fuzzy control system for heating and ventilation (HVAC) systems within a building. Each local control loop is affected by a number of local variables, as well as information from neighboring controllers. By including this additional information it is hoped that a more equal allocation of resources can be achieved.

Development of a wearable assistive soft robotic device for elbow rehabilitation

The loss of motor function at the elbow joint can result as a consequence of stroke. Stroke is a clinical illness resulting in long lasting neurological deficits often affecting somatosensory and motor cortices. More than half of those that recover from a stroke survive with disability in their upper arm and need rehabilitation therapy to help in regaining functions of daily living. In this paper, we demonstrated a prototype of a low-cost, ultra-light and wearable soft robotic assistive device that could aid administration of elbow motion therapies to stroke patients. In order to assist the rotation of the elbow joint, the soft modules which consist of soft wedge-like cellular units was inflated by air to produce torque at the elbow joint. Highly compliant rotation can be naturally realised by the elastic property of soft silicone and pneumatic control of air. Based on the direct visual-actuation control, a higher control loop utilised visual processing to apply positional control, the lower control loop was implemented by an electronic circuit to achieve the desired pressure of the soft modules by Pulse Width Modulation. To examine the functionality of the proposed soft modular system, we used an anatomical model of the upper limb and performed the experiments with healthy participants.

Uma proposta de regulador nebuloso para geradores eólicos de indução

This work presents a proposal for a voltage and frequency control system for a wind power induction generator. It has been developed na experimental structure composes basically by a three phase induction machine, a three phase capacitor and a reactive static Power compensator controlled by histeresys. lt has been developed control algorithms using conventional methods (Pl control) and linguistic methods (using concepts of logic and fuzzy control), to compare their performances in the variable speed generator system. The control loop was projected using the ADJDA PCL 818 model board into a Pentium 200 MHz compu ter. The induction generator mathematical model was studied throught Park transformation. It has been realized simulations in the Pspice@ software, to verify the system characteristics in transient and steady-state situations. The real time control program was developed in C language, possibilish verify the algorithm performance in the 2,2kW didatic experimental system

Técnica de controle adaptativo robusto aplicada a filtros ativos de potência e paralelo

The Methods for compensation of harmonic currents and voltages have been widely used since these methods allow to reduce to acceptable levels the harmonic distortion in the voltages or currents in a power system, and also compensate reactive. The reduction of harmonics and reactive contributes to the reduction of losses in transmission lines and electrical machinery, increasing the power factor, reduce the occurrence of overvoltage and overcurrent. The active power filter is the most efficient method for compensation of harmonic currents and voltages. The active power filter is necessary to use current and voltage controllers loop. Conventionally, the current and voltage control loop of active filter has been done by proportional controllers integrative. This work, investigated the use of a robust adaptive control technique on the shunt active power filter current and voltage control loop to increase robustness and improve the performance of active filter to compensate for harmonics. The proposed control scheme is based on a combination of techniques for adaptive control pole placement and variable structure. The advantages of the proposed method over conventional ones are: lower total harmonic distortion, more flexibility, adaptability and robustness to the system. Moreover, the proposed control scheme improves the performance and improves the transient of active filter. The validation of the proposed technique was verified initially by a simulation program implemented in C++ language and then experimental results were obtained using a prototype three-phase active filter of 1 kVA

Uma abordagem dirigida por modelos para desenvolvimento de middlewares auto-adaptativos para transmissão de fluxo de dados baseado em restrições de QoS

The use of middleware technology in various types of systems, in order to abstract low-level details related to the distribution of application logic, is increasingly common. Among several systems that can be benefited from using these components, we highlight the distributed systems, where it is necessary to allow communications between software components located on different physical machines. An important issue related to the communication between distributed components is the provision of mechanisms for managing the quality of service. This work presents a metamodel for modeling middlewares based on components in order to provide to an application the abstraction of a communication between components involved in a data stream, regardless their location. Another feature of the metamodel is the possibility of self-adaptation related to the communication mechanism, either by updating the values of its configuration parameters, or by its replacement by another mechanism, in case of the restrictions of quality of service specified are not being guaranteed. In this respect, it is planned the monitoring of the communication state (application of techniques like feedback control loop), analyzing performance metrics related. The paradigm of Model Driven Development was used to generate the implementation of a middleware that will serve as proof of concept of the metamodel, and the configuration and reconfiguration policies related to the dynamic adaptation processes. In this sense was defined the metamodel associated to the process of a communication configuration. The MDD application also corresponds to the definition of the following transformations: the architectural model of the middleware in Java code, and the configuration model to XML