881 resultados para Hybrid system approach
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An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.
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Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfilment of the requirements for the degree of Master in Computer Science
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Dissertation to obtain the degree of Doctor in Electrical and Computer Engineering, specialization of Collaborative Networks
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In today’s highly competitive market, it is critical to provide customers services with a high level of configuration to answer their business needs. Knowing in advance the performance associated with a specific choreography of services (e.g., by taking into account the expected results of each component service) represents an important asset that allows businesses to provide a global service tailored to customers’ specific requests. This research work aims at advancing the state-of-the-art in this area by proposing an approach for service selection and ranking using services choreography, predicting the behavior of the services considering customers’ requirements and preferences, business process constraints and characteristics of the execution environment.
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Dissertation submitted in partial fulfillment of the requirements for degree of Master in Statistics and Information Management.
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Atualmente, os guias turísticos são constituídos por diversos módulos, nomeadamente, módulos de recomendação e de modelação do utilizador. Estes ajudam a adaptar melhor as recomendações dadas ao utilizador de acordo com as suas preferências. A necessidade de adaptar os guias turísticos às possíveis necessidades de saúde do utilizador, foi a motivação para a realização desta dissertação. Quando alguém visita um local desconhecido, considera normalmente as condições tanto de alojamento como de alimentação desse local. Contudo, se por algum motivo, necessita de cuidados de saúde, essa pessoa não se encontra preparada para isso. Assim, a recomendação de uma instituição de saúde direcionada para o turista é uma solução possível para o problema encontrado. Pretendeu-se desenvolver um módulo de recomendação híbrido no âmbito da prestação de informações relacionadas com as possíveis necessidades de saúde do turista, tendo em conta o seu perfil. Para a sua implementação seguiu-se a abordagem baseada em conteúdo e técnicas de classificação das instituições de saúde a recomendar ao utilizador. O protótipo desenvolvido foi testado com alguns utilizadores em termos de funcionalidades. Finalmente, pretende-se que o protótipo seja testado com mais utilizadores, possuidores de diversas características em termos de condições de mobilidade, historial clínico e necessidades. Estes testes irão permitir avaliar o protótipo ao nível da qualidade da recomendação prestada. Poder-se-á, assim, atingir o objetivo relativo à integração deste protótipo num sistema de recomendação de apoio ao turista utilizado pela Câmara Municipal do Porto.
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Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.
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Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.
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While fractional calculus (FC) is as old as integer calculus, its application has been mainly restricted to mathematics. However, many real systems are better described using FC equations than with integer models. FC is a suitable tool for describing systems characterised by their fractal nature, long-term memory and chaotic behaviour. It is a promising methodology for failure analysis and modelling, since the behaviour of a failing system depends on factors that increase the model’s complexity. This paper explores the proficiency of FC in modelling complex behaviour by tuning only a few parameters. This work proposes a novel two-step strategy for diagnosis, first modelling common failure conditions and, second, by comparing these models with real machine signals and using the difference to feed a computational classifier. Our proposal is validated using an electrical motor coupled with a mechanical gear reducer.
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This paper employs the Lyapunov direct method for the stability analysis of fractional order linear systems subject to input saturation. A new stability condition based on saturation function is adopted for estimating the domain of attraction via ellipsoid approach. To further improve this estimation, the auxiliary feedback is also supported by the concept of stability region. The advantages of the proposed method are twofold: (1) it is straightforward to handle the problem both in analysis and design because of using Lyapunov method, (2) the estimation leads to less conservative results. A numerical example illustrates the feasibility of the proposed method.
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In this work the mission control and supervision system developed for the ROAZ Autonomous Surface Vehicle is presented. Complexity in mission requirements coupled with flexibility lead to the design of a modular hierarchical mission control system based on hybrid systems control. Monitoring and supervision control for a vehicle such as ROAZ mission is not an easy task using tools with low complexity and yet powerful enough. A set of tools were developed to perform both on board mission control and remote planning and supervision. “ROAZ- Mission Control” was developed to be used in support to bathymetric and security missions performed in river and at seas.
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OCEANS, 2001. MTS/IEEE Conference and Exhibition (Volume:2 )
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A control framework enabling the automated maneuvering of a Remotely Operate Vehicle (ROV) is presented. The control architecture is structured according to the principle of composition of vehicle motions from a minimal set of elemental maneuvers that are designed and verified independently. The principled approach is based on distributed hybrid systems techniques, and spans integrated design, simulation and implementation as the same model is used throughout. Hybrid systems control techniques are used to synthesize the elemental maneuvers and to design protocols, which coordinate the execution of elemental maneuvers within a complex maneuver. This work is part of the Inspection of Underwater Structures (IES) project whose main objective is the implementation of a ROV-based system for the inspection of underwater structures.
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OCEANS 2003. Proceedings (Volume:1 )
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Robotica 2012: 12th International Conference on Autonomous Robot Systems and Competitions April 11, 2012, Guimarães, Portugal