Control of a 6-DOF parallel manipulator through a mechatronic approach

This paper shows that a hierarchical architecture, distributing several control actions in growing levels of complexity and using resources of reconfigurable computing, enables one to take into account the ease of future modifications, updates and improvements in robotic applications. An experimental example of a Stewart—Gough platform control (a platform applied as the solution to countless practical problems) is presented using reconfigurable computing. The software and hardware developed are structured in independent blocks. This open architecture implementation allows easy expansion of the system and better adaptation of the platform to its related tasks.

From cheating to teaching: a path for conversion of illegal gambling machines

Video poker machines, a former symbol of fraud and gambling in Brazil, are now being converted into computer-based educational tools for Brazilian public primary schools and also for governmental and non-governmental institutions dealing with communities of poverty and social exclusion, in an attempt to reduce poverty risks (decrease money spent on gambling) and promote social inclusion (increase access and motivation to education). Thousands of illegal gambling machines are seized by federal authorities, in Brazil, every year, and usually destroyed at the end of the criminal apprehension process. This paper describes a project developed by the University of Southern Santa Catarina, Brazil, responsible for the conversion process of gambling machines, and the social inclusion opportunities derived from it. All project members worked on a volunteer basis, seeking to promote social inclusion of Brazilian young boys and girls, namely through digital inclusion. So far, the project has been able to convert over 200 gambling machines and install them in over 40 public primary schools, thus directly benefiting more than 12,000 schoolchildren. The initial motivation behind this project was technology based, however the different options arising from the conversion process of the gambling machines have also motivated a rather innovative and unique experience in allowing schoolchildren and young people with special (educational) needs to access to computer-based pedagogical applications. The availability of these converted machines also helps to place Information and Communication Technologies (ICT) in the very daily educational environment of these children and youngsters, thus serving social and cultural inclusion aspects, by establishing a dialogue with the community and their technological expectations, and also directly contributing to their digital literacy.

Aplicação do multi-layer stream mapping para a gestão da eficiência de recursos e produtividade de um sistema de produção

Mestrado em Engenharia Mecânica – Especialização Gestão Industrial

Multi-objective Parallel Particle Swarm Optimization for Day-ahead Vehicle-To-Grid Scheduling

This paper presents a methodology for multi-objective day-ahead energy resource scheduling for smart grids considering intensive use of distributed generation and Vehicle- To-Grid (V2G). The main focus is the application of weighted Pareto to a multi-objective parallel particle swarm approach aiming to solve the dual-objective V2G scheduling: minimizing total operation costs and maximizing V2G income. A realistic mathematical formulation, considering the network constraints and V2G charging and discharging efficiencies is presented and parallel computing is applied to the Pareto weights. AC power flow calculation is included in the metaheuristics approach to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

Strategic Bidding for Electricity Markets Negotiation Using Support Vector Machines

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which simulates the electricity markets environment. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator.

Solar Intensity Forecasting using Artificial Neural Networks and Support Vector Machines

This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.

Short-term Wind Speed Forecasting using Support Vector Machines

Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.

Tolerância a falhas em sistemas de tempo-real distribuídos e embebidos

Este documento descreve um modelo de tolerância a falhas para sistemas de tempo-real distribuídos. A sugestão deste modelo tem como propósito a apresentação de uma solu-ção fiável, flexível e adaptável às necessidades dos sistemas de tempo-real distribuídos. A tolerância a falhas é um aspeto extremamente importante na construção de sistemas de tempo-real e a sua aplicação traz inúmeros benefícios. Um design orientado para a to-lerância a falhas contribui para um melhor desempenho do sistema através do melhora-mento de aspetos chave como a segurança, a confiabilidade e a disponibilidade dos sis-temas. O trabalho desenvolvido centra-se na prevenção, deteção e tolerância a falhas de tipo ló-gicas (software) e físicas (hardware) e assenta numa arquitetura maioritariamente basea-da no tempo, conjugada com técnicas de redundância. O modelo preocupa-se com a efi-ciência e os custos de execução. Para isso utilizam-se também técnicas tradicionais de to-lerância a falhas, como a redundância e a migração, no sentido de não prejudicar o tempo de execução do serviço, ou seja, diminuindo o tempo de recuperação das réplicas, em ca-so de ocorrência de falhas. Neste trabalho são propostas heurísticas de baixa complexida-de para tempo-de-execução, a fim de se determinar para onde replicar os componentes que constituem o software de tempo-real e de negociá-los num mecanismo de coordena-ção por licitações. Este trabalho adapta e estende alguns algoritmos que fornecem solu-ções ainda que interrompidos. Estes algoritmos são referidos em trabalhos de investiga-ção relacionados, e são utilizados para formação de coligações entre nós coadjuvantes. O modelo proposto colmata as falhas através de técnicas de replicação ativa, tanto virtual como física, com blocos de execução concorrentes. Tenta-se melhorar ou manter a sua qualidade produzida, praticamente sem introduzir overhead de informação significativo no sistema. O modelo certifica-se que as máquinas escolhidas, para as quais os agentes migrarão, melhoram iterativamente os níveis de qualidade de serviço fornecida aos com-ponentes, em função das disponibilidades das respetivas máquinas. Caso a nova configu-ração de qualidade seja rentável para a qualidade geral do serviço, é feito um esforço no sentido de receber novos componentes em detrimento da qualidade dos já hospedados localmente. Os nós que cooperam na coligação maximizam o número de execuções para-lelas entre componentes paralelos que compõem o serviço, com o intuito de reduzir atra-sos de execução. O desenvolvimento desta tese conduziu ao modelo proposto e aos resultados apresenta-dos e foi genuinamente suportado por levantamentos bibliográficos de trabalhos de in-vestigação e desenvolvimento, literaturas e preliminares matemáticos. O trabalho tem também como base uma lista de referências bibliográficas.

Methodologies for the WCET Analysis of Parallel Applications on Many-core Architectures

Euromicro Conference on Digital System Design (DSD 2015), Funchal, Portugal.

Online Admission of Parallel Real-Time Tasks

6th Real-Time Scheduling Open Problems Seminar (RTSOPS 2015), Lund, Sweden.

A Multi-DAG Model for Real-Time Parallel Applications with Conditional Execution

The 30th ACM/SIGAPP Symposium On Applied Computing (SAC 2015). 13 to 17, Apr, 2015, Embedded Systems. Salamanca, Spain.

Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures supported by an FTT-SE Network

Distributed real-time systems such as automotive applications are becoming larger and more complex, thus, requiring the use of more powerful hardware and software architectures. Furthermore, those distributed applications commonly have stringent real-time constraints. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed real-time tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time.

P-SOCRATES: A parallel software framework for time-critical many-core systems

Article in Press, Corrected Proof

Towards the Combination of Work-Stealing and Semi-Partitioned Scheduling for Parallel Tasks

Paper/Poster presented in Work in Progress Session, 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 26, Mar, 2015. Porto, Portugal.

Towards the Combination of Work-Stealing and Semi-Partitioned Scheduling for Parallel Tasks

Poster presented in Work in Progress Session, 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 26, Mar, 2015. Porto, Portugal.