914 resultados para Neural Control Systems
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Proceedings of the 10th Conference on Dynamical Systems Theory and Applications
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Neste documento descreve-se o projeto desenvolvido na unidade curricular de Tese e Dissertação durante o 2º ano do Mestrado de Engenharia Eletrotécnica e de Computadores no ramo de Automação e Sistemas, no Departamento de Engenharia Eletrotécnica (DEE) do Instituto Superior de Engenharia do Porto (ISEP). O projeto escolhido teve como base o uso da tecnologia das redes neuronais para implementação em sistemas de controlo. Foi necessário primeiro realizar um estudo desta tecnologia, perceber como esta surgiu e como é estruturada. Por último, abordar alguns casos de estudo onde as redes neuronais foram aplicadas com sucesso. Relativamente à implementação, foram consideradas diferentes estruturas de controlo, e entre estas escolhidas a do sistema de controlo estabilizador e sistema de referência adaptativo. No entanto, como o objetivo deste trabalho é o estudo de desempenho quando aplicadas as redes neuronais, não se utilizam apenas estas como controlador. A análise exposta neste trabalho trata de perceber em que medida é que a introdução das redes neuronais melhora o controlo de um processo. Assim sendo, os sistemas de controlo utilizados devem conter pelo menos uma rede neuronal e um controlador PID. Os testes de desempenho são aplicados no controlo de um motor DC, sendo realizados através do recurso ao software MATLAB. As simulações efetuadas têm diferentes configurações de modo a tirar conclusões o mais gerais possível. Assim, os sistemas de controlo são simulados para dois tipos de entrada diferentes, e com ou sem a adição de ruído no sensor. Por fim, é efetuada uma análise das respostas de cada sistema implementado e calculados os índices de desempenho das mesmas.
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21th Annual Conference of the International Group for Lean Construction (IGLC 21), July 2013, Fortaleza, Brazil
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Solar photovoltaic systems are an increasing option for electricity production, since they produce electrical energy from a clean renewable energy resource, and over the years, as a result of the research, their efficiency has been increasing. For the interface between the dc photovoltaic solar array and the ac electrical grid is necessary the use of an inverter (dc-ac converter), which should be optimized to extract the maximum power from the photovoltaic solar array. In this paper is presented a solution based on a current-source inverter (CSI) using continuous control set model predictive control (CCS-MPC). All the power circuits and respective control systems are described in detail along the paper and were tested and validated performing computer simulations. The paper shows the simulation results and are drawn several conclusions.
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The purpose of this study was to evaluate the determinism of the AS-lnterface network and the 3 main families of control systems, which may use it, namely PLC, PC and RTOS. During the course of this study the PROFIBUS and Ethernet field level networks were also considered in order to ensure that they would not introduce unacceptable latencies into the overall control system. This research demonstrated that an incorrectly configured Ethernet network introduces unacceptable variable duration latencies into the control system, thus care must be exercised if the determinism of a control system is not to be compromised. This study introduces a new concept of using statistics and process capability metrics in the form of CPk values, to specify how suitable a control system is for a given control task. The PLC systems, which were tested, demonstrated extremely deterministic responses, but when a large number of iterations were introduced in the user program, the mean control system latency was much too great for an AS-I network. Thus the PLC was found to be unsuitable for an AS-I network if a large, complex user program Is required. The PC systems, which were tested were non-deterministic and had latencies of variable duration. These latencies became extremely exaggerated when a graphing ActiveX was included in the control application. These PC systems also exhibited a non-normal frequency distribution of control system latencies, and as such are unsuitable for implementation with an AS-I network. The RTOS system, which was tested, overcame the problems identified with the PLC systems and produced an extremely deterministic response, even when a large number of iterations were introduced in the user program. The RTOS system, which was tested, is capable of providing a suitable deterministic control system response, even when an extremely large, complex user program is required.
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Consider a Riemannian manifold equipped with an infinitesimal isometry. For this setup, a unified treatment is provided, solely in the language of Riemannian geometry, of techniques in reduction, linearization, and stability of relative equilibria. In particular, for mechanical control systems, an explicit characterization is given for the manner in which reduction by an infinitesimal isometry, and linearization along a controlled trajectory "commute." As part of the development, relationships are derived between the Jacobi equation of geodesic variation and concepts from reduction theory, such as the curvature of the mechanical connection and the effective potential. As an application of our techniques, fiber and base stability of relative equilibria are studied. The paper also serves as a tutorial of Riemannian geometric methods applicable in the intersection of mechanics and control theory.
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El projecte "Anàlisi del sistema operatiu RTLinux i implementació d'un entorn de desenvolupament de tasques en temps real" analitza la possibilitat de crear un entorn de desenvolupament de tasques en temps real per poder crear sistemes de control complex, tot això mitjançant codi lliure. Inicialment es fa un aprenentatge sobre el concepte de temps real, després s'elegeix el sistema operatiu en temps real RTLinux per a crear l'entorn de desenvolupament utilitzant el llenguatge de programació Tcl/Tk. Es creen un conjunt d'aplicacions (pel control computacional) per estudiar la viabilitat de la construcció de l'entorn desitjat per facilitar la tasca de l'usuari final. Aquest projecte obre multitud de possibles camins a continuar: comunicació remota, implementació de planificadors, estudi de controladors, etc.
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El objetivo del proyecto es diseñar una plataforma de ensayos para la simulación de vuelos de vehículos aeroespaciales. La plataforma permitirá diseñar y evaluar los algoritmos de navegación, guiado y control de los vehículos aeroespaciales modelados en la plataforma de simulación, focalizando el trabajo de los ingenieros en el modelado de vehículos y en el desarrollo de sistemas de control digital. La memoria recoge las fases de un proyecto de ingeniería del software, describiendo el plan de proyecto, el análisis del sistema, la especificación de requisitos y el diseño del mismo.
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Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task
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This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task
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This paper presents a complete control architecture that has been designed to fulfill predefined missions with an autonomous underwater vehicle (AUV). The control architecture has three levels of control: mission level, task level and vehicle level. The novelty of the work resides in the mission level, which is built with a Petri network that defines the sequence of tasks that are executed depending on the unpredictable situations that may occur. The task control system is composed of a set of active behaviours and a coordinator that selects the most appropriate vehicle action at each moment. The paper focuses on the design of the mission controller and its interaction with the task controller. Simulations, inspired on an industrial underwater inspection of a dam grate, show the effectiveness of the control architecture
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This paper surveys control architectures proposed in the literature and describes a control architecture that is being developed for a semi-autonomous underwater vehicle for intervention missions (SAUVIM) at the University of Hawaii. Conceived as hybrid, this architecture has been organized in three layers: planning, control and execution. The mission is planned with a sequence of subgoals. Each subgoal has a related task supervisor responsible for arranging a set of pre-programmed task modules in order to achieve the subgoal. Task modules are the key concept of the architecture. They are the main building blocks and can be dynamically re-arranged by the task supervisor. In our architecture, deliberation takes place at the planning layer while reaction is dealt through the parallel execution of the task modules. Hence, the system presents both a hierarchical and an heterarchical decomposition, being able to show a predictable response while keeping rapid reactivity to the dynamic environment
Identification and Semiactive Control of Smart Structures Equipped with Magnetorheological Actuators
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This paper deals with the problem of identification and semiactive control of smart structures subject to unknown external disturbances such as earthquake, wind, etc. The experimental setup used is a 6-story test structure equipped with shear-mode semiactive magnetorheological actuators being installed in WUSCEEL. The experimental results obtained have verified the effectiveness of the proposed control algorithms
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This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model