997 resultados para Controlador PID
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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This monograph proposes the implementation of a low cost PID controller utilizing a PIC microcontroller, and its application in a positioning system previously controlled by a dedicated integrated circuit for a positioning system. Applying the closed-loop PID control, the system instability was reduced, and its response was smoother, eliminating vibrations and mechanical wear compared to its response with the dedicated integrated circuit, which has a very limited control action. The actuator of the system is a DC motor, whose speed is controlled by the Pulse Width Modulation (PWM) technique, using a Full-Bridge circuit, allowing the shift of direction of rotation. The utilized microcontroller was the PIC16F684, which has an enhanced PWM module, with its analog converters used as reference and position feedback. The positioning sensor is a multiturn potentiometer coupled to the motor axis by gears. The possibility of programming the PID coefficients in the microcontroller, as well as the adjustment of the sampling rate, allows the implemented system achieving high level of versatility
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Tesis (Ingeniero(a) Eléctrico).--Universidad de La Salle. Facultad de Ingeniería. Programa de Ingeniería Eléctrica, 2014
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Pós-graduação em Engenharia Mecânica - FEG
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La robótica móvil constituye un área de desarrollo y explotación de interés creciente. Existen ejemplos de robótica móvil de relevancia destacada en el ámbito industrial y se estima un fuerte crecimiento en el terreno de la robótica de servicios. En la arquitectura software de todos los robots móviles suelen aparecer con frecuencia componentes que tienen asignadas competencias de gobierno, navegación, percepción, etcétera, todos ellos de importancia destacada. Sin embargo, existe un elemento, difícilmente prescindible en este tipo de robots, el cual se encarga del control de velocidad del dispositivo en sus desplazamientos. En el presente proyecto se propone desarrollar un controlador PID basado en el modelo y otro no basado en el modelo. Dichos controladores deberán operar en un robot con configuración de triciclo disponible en el Departamento de Sistemas Informáticos y deberán por tanto ser programados en lenguaje C para ejecutar en el procesador digital de señal destinado para esa actividad en el mencionado robot (dsPIC33FJ128MC802). ABSTRACT Mobile robotics constitutes an area of development and exploitation of increasing interest. There are examples of mobile robotics of outstanding importance in industry and strong growth is expected in the field of service robotics. In the software architecture of all mobile robots usually appear components which have assigned competences of government, navigation, perceptionetc., all of them of major importance. However, there is an essential element in this type of robots, which takes care of the speed control. The present project aims to develop a model-based and other non-model-based PID controller. These controllers must operate in a robot with tricycle settings, available from the Department of Computing Systems, and should therefore be programmed in C language to run on the digital signal processor dedicated to that activity in the robot (dsPIC33FJ128MC802).
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Fuzzy logic controllers (FLC) are intelligent systems, based on heuristic knowledge, that have been largely applied in numerous areas of everyday life. They can be used to describe a linear or nonlinear system and are suitable when a real system is not known or too difficult to find their model. FLC provide a formal methodology for representing, manipulating and implementing a human heuristic knowledge on how to control a system. These controllers can be seen as artificial decision makers that operate in a closed-loop system, in real time. The main aim of this work was to develop a single optimal fuzzy controller, easily adaptable to a wide range of systems – simple to complex, linear to nonlinear – and able to control all these systems. Due to their efficiency in searching and finding optimal solution for high complexity problems, GAs were used to perform the FLC tuning by finding the best parameters to obtain the best responses. The work was performed using the MATLAB/SIMULINK software. This is a very useful tool that provides an easy way to test and analyse the FLC, the PID and the GAs in the same environment. Therefore, it was proposed a Fuzzy PID controller (FL-PID) type namely, the Fuzzy PD+I. For that, the controller was compared with the classical PID controller tuned with, the heuristic Ziegler-Nichols tuning method, the optimal Zhuang-Atherton tuning method and the GA method itself. The IAE, ISE, ITAE and ITSE criteria, used as the GA fitness functions, were applied to compare the controllers performance used in this work. Overall, and for most systems, the FL-PID results tuned with GAs were very satisfactory. Moreover, in some cases the results were substantially better than for the other PID controllers. The best system responses were obtained with the IAE and ITAE criteria used to tune the FL-PID and PID controllers.
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The present work has as objective to present a method of project and implementation of controllers PID, based on industrial instrumentation. An automatic system of auto-tunning of controllers PID will be presented, for systems of first and second order. The software presented in this work is applied in controlled plants by PID controllers implemented in a CLP. Software is applied to make the auto-tunning of the parameters of controller PID of plants that need this tunning. Software presents two stages, the first one is the stage of identification of the system using the least square recursive algorithm and the second is the stage of project of the parameters of controller PID using the root locus algorithm. An important fact of this work is the use of industrial instrumentation for the accomplishment of the experiments. The experiments had been carried through in controlled real plants for controllers PID implemented in the CLP. Thus has not only one resulted obtained with theoreticians experiments made with computational programs, and yes resulted obtained of real systems. The experiments had shown good results gotten with developed software
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The main objective of work is to show procedures to implement intelligent control strategies. This strategies are based on fuzzy scheduling of PID controllers, by using only standard function blocks of this technology. Then, the standardization of Foundation Fieldbus is kept. It was developed an environment to do the necessary tests, it validates the propose. This environment is hybrid, it has a real module (the fieldbus) and a simulated module (the process), although the control signals and measurement are real. Then, it is possible to develop controllers projects. In this work, a fuzzy supervisor was developed to schedule a network of PID controller for a non-linear plant. Analyzing its performance results to the control and regulation problem
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Dissertação de dout. em Electrónica e Computação, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2004
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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.
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Mestrado em engenharia electrotécnica e de computadores - Área de Especialização de Sistemas Autónomos