447 research outputs found

    Self-organizing fuzzy sliding-mode control for a voice coil motor

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    [[abstract]]Voice coil motor (VCM) is widely known as its topquality of free friction, low noise, fast transient response and well repeatability. Yet the dynamic characteristic of a VCM is nonlinear and time-varying, thus the model-based conventional controller is difficult to achieve high-precision control performance for a VCM. To attack this problem, a selforganizing fuzzy sliding-mode control (SFSC) system is proposed in this paper. All of the fuzzy rules are online grown and pruned by the structure learning phase and the parameter learning phase is designed to tune the controller parameter in the gradient-descent-learning algorithm. From the experiment results, it shows that the proposed SFSC system can successfully control a VCM with favorable control response with enhanced disturbance rejection performance.[[notice]]補正完畢[[conferencetype]]國際[[conferencedate]]April 9-11[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]Taipei, Taiwa

    Line-of-sight-stabilization and tracking control for inertial platforms

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    Nowadays, line of sight stabilization and tracking using inertially stabilized platforms (ISPs) are still challenging engineering problems. With a growing demand for high-precision applications, more involved control techniques are necessary to achieve better performance. In this work, kinematic and dynamic models for a three degrees-of-freedom ISP are presented. These models are based in the vehicle-manipulator system (VMS) framework for modeling of robot manipulators operating in a mobile base (vehicles). The dynamic model follows the Euler-Lagrange formulation and is implemented by numeric simulations using the iterative Newton-Euler method. Two distinct control strategies for both stabilization and tracking are proposed: (i) computed torque control and (ii) sliding mode control using the recent SuperTwisting Algorithm (STA) combined with a High-Order Sliding Mode Observer (HOSMO). Simulations using data from a simulated vessel allow us to compare the performance of the computed torque controllers with respect to the commonly used P-PI controller. Besides, the results obtained for the sliding mode controllers indicate that the Super-Twisting algorithm offers ideal robustness to the vehicle motion disturbances and also to parametric uncertainties, resulting in a stabilization precision of approximately 0,8 mrad.Hoje em dia, a estabilização e o rastreamento da linha de visada utilizando plataformas inerciais continuam a constituir desafiadores problemas de engenharia. Com a crescente demanda por aplicações de alta precisão, técnicas de controle complexas são necessárias para atingir melhor desempenho. Neste trabalho, modelos cinemáticos e dinâmicos para uma plataforma mecânica de estabilização inercial são apresentados. Tais modelos se baseiam no formalismo para sistemas veículo-manipulator para a modelagem de manipuladores robóticos operando em uma base móvel (veículo). O modelo dinâmico apresentado segue a formulação analítica de Euler-Lagrange e é implementado em simulações numéricas através do método iterativo de Newton-Euler. Duas estratégias de controle distintas para estabilização e rastreamento são propostas: (i) controle por torque-computado e (ii) controle por modos deslizantes utilizando o recente algoritmo Super-Twisting combinado com um observador baseado em modos deslizantes de alta ordem. Simulações utilizando dados de movimentação de um navio simulado permitem comparar o desempenho dos controladores por torque computado em relação a um tipo comum de controlador linear utilizado na literatura: o P-PI. Além disso, os resultados obtidos para o controle por modos deslizantes permitem concluir que o algoritmo Super-Twisting apresenta rejeição ideal a perturbações provenientes do movimento do veículo e também a incertezas paramétricas, resultando em precisão de estabilização de aproximadamente 0,8 mrad

    Emotional Fuzzy Sliding-Mode Control for Unknown Nonlinear Systems

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    [[abstract]]The brain emotional learning model can be implemented with a simple hardware and processor; however, the learning model cannot model the qualitative aspects of human knowledge. To solve this problem, a fuzzy-based emotional learning model (FELM) with structure and parameter learning is proposed. The membership functions and fuzzy rules can be learned through the derived learning scheme. Further, an emotional fuzzy sliding-mode control (EFSMC) system, which does not need the plant model, is proposed for unknown nonlinear systems. The EFSMC system is applied to an inverted pendulum and a chaotic synchronization. The simulation results with the use of EFSMC system demonstrate the feasibility of FELM learning procedure. The main contributions of this paper are (1) the FELM varies its structure dynamically with a simple computation; (2) the parameter learning imitates the role of emotions in mammalians brain; (3) by combining the advantage of nonsingular terminal sliding-mode control, the EFSMC system provides very high precision and finite-time control performance; (4) the system analysis is given in the sense of the gradient descent method.[[notice]]補正完

    FPGA design methodology for industrial control systems—a review

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    This paper reviews the state of the art of fieldprogrammable gate array (FPGA) design methodologies with a focus on industrial control system applications. This paper starts with an overview of FPGA technology development, followed by a presentation of design methodologies, development tools and relevant CAD environments, including the use of portable hardware description languages and system level programming/design tools. They enable a holistic functional approach with the major advantage of setting up a unique modeling and evaluation environment for complete industrial electronics systems. Three main design rules are then presented. These are algorithm refinement, modularity, and systematic search for the best compromise between the control performance and the architectural constraints. An overview of contributions and limits of FPGAs is also given, followed by a short survey of FPGA-based intelligent controllers for modern industrial systems. Finally, two complete and timely case studies are presented to illustrate the benefits of an FPGA implementation when using the proposed system modeling and design methodology. These consist of the direct torque control for induction motor drives and the control of a diesel-driven synchronous stand-alone generator with the help of fuzzy logic

    Visual Servoing

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    The goal of this book is to introduce the visional application by excellent researchers in the world currently and offer the knowledge that can also be applied to another field widely. This book collects the main studies about machine vision currently in the world, and has a powerful persuasion in the applications employed in the machine vision. The contents, which demonstrate that the machine vision theory, are realized in different field. For the beginner, it is easy to understand the development in the vision servoing. For engineer, professor and researcher, they can study and learn the chapters, and then employ another application method

    Advances in Spacecraft Systems and Orbit Determination

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    "Advances in Spacecraft Systems and Orbit Determinations", discusses the development of new technologies and the limitations of the present technology, used for interplanetary missions. Various experts have contributed to develop the bridge between present limitations and technology growth to overcome the limitations. Key features of this book inform us about the orbit determination techniques based on a smooth research based on astrophysics. The book also provides a detailed overview on Spacecraft Systems including reliability of low-cost AOCS, sliding mode controlling and a new view on attitude controller design based on sliding mode, with thrusters. It also provides a technological roadmap for HVAC optimization. The book also gives an excellent overview of resolving the difficulties for interplanetary missions with the comparison of present technologies and new advancements. Overall, this will be very much interesting book to explore the roadmap of technological growth in spacecraft systems

    Vision-Based navigation system for unmanned aerial vehicles

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    Mención Internacional en el título de doctorThe main objective of this dissertation is to provide Unmanned Aerial Vehicles (UAVs) with a robust navigation system; in order to allow the UAVs to perform complex tasks autonomously and in real-time. The proposed algorithms deal with solving the navigation problem for outdoor as well as indoor environments, mainly based on visual information that is captured by monocular cameras. In addition, this dissertation presents the advantages of using the visual sensors as the main source of data, or complementing other sensors in providing useful information; in order to improve the accuracy and the robustness of the sensing purposes. The dissertation mainly covers several research topics based on computer vision techniques: (I) Pose Estimation, to provide a solution for estimating the 6D pose of the UAV. This algorithm is based on the combination of SIFT detector and FREAK descriptor; which maintains the performance of the feature points matching and decreases the computational time. Thereafter, the pose estimation problem is solved based on the decomposition of the world-to-frame and frame-to-frame homographies. (II) Obstacle Detection and Collision Avoidance, in which, the UAV is able to sense and detect the frontal obstacles that are situated in its path. The detection algorithm mimics the human behaviors for detecting the approaching obstacles; by analyzing the size changes of the detected feature points, combined with the expansion ratios of the convex hull constructed around the detected feature points from consecutive frames. Then, by comparing the area ratio of the obstacle and the position of the UAV, the method decides if the detected obstacle may cause a collision. Finally, the algorithm extracts the collision-free zones around the obstacle, and combining with the tracked waypoints, the UAV performs the avoidance maneuver. (III) Navigation Guidance, which generates the waypoints to determine the flight path based on environment and the situated obstacles. Then provide a strategy to follow the path segments and in an efficient way and perform the flight maneuver smoothly. (IV) Visual Servoing, to offer different control solutions (Fuzzy Logic Control (FLC) and PID), based on the obtained visual information; in order to achieve the flight stability as well as to perform the correct maneuver; to avoid the possible collisions and track the waypoints. All the proposed algorithms have been verified with real flights in both indoor and outdoor environments, taking into consideration the visual conditions; such as illumination and textures. The obtained results have been validated against other systems; such as VICON motion capture system, DGPS in the case of pose estimate algorithm. In addition, the proposed algorithms have been compared with several previous works in the state of the art, and are results proves the improvement in the accuracy and the robustness of the proposed algorithms. Finally, this dissertation concludes that the visual sensors have the advantages of lightweight and low consumption and provide reliable information, which is considered as a powerful tool in the navigation systems to increase the autonomy of the UAVs for real-world applications.El objetivo principal de esta tesis es proporcionar Vehiculos Aereos no Tripulados (UAVs) con un sistema de navegacion robusto, para permitir a los UAVs realizar tareas complejas de forma autonoma y en tiempo real. Los algoritmos propuestos tratan de resolver problemas de la navegacion tanto en ambientes interiores como al aire libre basandose principalmente en la informacion visual captada por las camaras monoculares. Ademas, esta tesis doctoral presenta la ventaja de usar sensores visuales bien como fuente principal de datos o complementando a otros sensores en el suministro de informacion util, con el fin de mejorar la precision y la robustez de los procesos de deteccion. La tesis cubre, principalmente, varios temas de investigacion basados en tecnicas de vision por computador: (I) Estimacion de la Posicion y la Orientacion (Pose), para proporcionar una solucion a la estimacion de la posicion y orientacion en 6D del UAV. Este algoritmo se basa en la combinacion del detector SIFT y el descriptor FREAK, que mantiene el desempeno del a funcion de puntos de coincidencia y disminuye el tiempo computacional. De esta manera, se soluciona el problema de la estimacion de la posicion basandose en la descomposicion de las homografias mundo a imagen e imagen a imagen. (II) Deteccion obstaculos y elusion colisiones, donde el UAV es capaz de percibir y detectar los obstaculos frontales que se encuentran en su camino. El algoritmo de deteccion imita comportamientos humanos para detectar los obstaculos que se acercan, mediante el analisis de la magnitud del cambio de los puntos caracteristicos detectados de referencia, combinado con los ratios de expansion de los contornos convexos construidos alrededor de los puntos caracteristicos detectados en frames consecutivos. A continuacion, comparando la proporcion del area del obstaculo y la posicion del UAV, el metodo decide si el obstaculo detectado puede provocar una colision. Por ultimo, el algoritmo extrae las zonas libres de colision alrededor del obstaculo y combinandolo con los puntos de referencia, elUAV realiza la maniobra de evasion. (III) Guiado de navegacion, que genera los puntos de referencia para determinar la trayectoria de vuelo basada en el entorno y en los obstaculos detectados que encuentra. Proporciona una estrategia para seguir los segmentos del trazado de una manera eficiente y realizar la maniobra de vuelo con suavidad. (IV) Guiado por Vision, para ofrecer soluciones de control diferentes (Control de Logica Fuzzy (FLC) y PID), basados en la informacion visual obtenida con el fin de lograr la estabilidad de vuelo, asi como realizar la maniobra correcta para evitar posibles colisiones y seguir los puntos de referencia. Todos los algoritmos propuestos han sido verificados con vuelos reales en ambientes exteriores e interiores, tomando en consideracion condiciones visuales como la iluminacion y las texturas. Los resultados obtenidos han sido validados con otros sistemas: como el sistema de captura de movimiento VICON y DGPS en el caso del algoritmo de estimacion de la posicion y orientacion. Ademas, los algoritmos propuestos han sido comparados con trabajos anteriores recogidos en el estado del arte con resultados que demuestran una mejora de la precision y la robustez de los algoritmos propuestos. Esta tesis doctoral concluye que los sensores visuales tienen las ventajes de tener un peso ligero y un bajo consumo y, proporcionar informacion fiable, lo cual lo hace una poderosa herramienta en los sistemas de navegacion para aumentar la autonomia de los UAVs en aplicaciones del mundo real.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Carlo Regazzoni.- Secretario: Fernando García Fernández.- Vocal: Pascual Campoy Cerver

    Advanced Strategies for Robot Manipulators

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    Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored
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