Optimal fuzzy PID control tuned with genetic algorithms

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.

Increase of the delivered energy probability in DES using a fuzzy probabilistic modeling

The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Power systems reliability calculation based on fuzzy data mining

This paper presents a methodology supported on the data base knowledge discovery process (KDD), in order to find out the failure probability of electrical equipments’, which belong to a real electrical high voltage network. Data Mining (DM) techniques are used to discover a set of outcome failure probability and, therefore, to extract knowledge concerning to the unavailability of the electrical equipments such us power transformers and high-voltages power lines. The framework includes several steps, following the analysis of the real data base, the pre-processing data, the application of DM algorithms, and finally, the interpretation of the discovered knowledge. To validate the proposed methodology, a case study which includes real databases is used. This data have a heavy uncertainty due to climate conditions for this reason it was used fuzzy logic to determine the set of the electrical components failure probabilities in order to reestablish the service. The results reflect an interesting potential of this approach and encourage further research on the topic.

Sistemas multimédia aplicados ao ensino da tradução – estudo de um caso

O uso recrudescente das novas tecnologias de informação conduziu ao aparecimento de novos ambientes de ensino, em que o computador, a internet, as intranets e o software específico ocuparam, em grande parte, o papel do manual e da sebenta, exigindo ao professor novas competências e estratégias. No Instituto Superior de Contabilidade e Administração do Porto, os Centros Multimédia de Línguas (CML) disponibilizam um conjunto de meios que abrangem áreas como o ensino da Legendagem, da Tradução Assistida por Computador, do ensino e aprendizagem de Línguas para Fins Específicos (também em regime de auto-aprendizagem) e, ainda numa fase piloto, do ensino à distância e apoio online. Para além de uma apresentação da experiência dos CML e de alguns dos resultados obtidos no que respeita ao ensino de Línguas Estrangeiras, da Interpretação e da Tradução, pretende-se reflectir sobre as novas necessidades do processo de ensino/aprendizagem, quer em termos da produção e disponibilização de conteúdos, quer em termos da avaliação. Finalmente, procurar-se-á aferir da adequação destas novas possibilidades ao sempre exigente e dinâmico mercado de trabalho.

Estudo comparativo entre criança com e sem joelhos valgos praticantes de hóquei em patins utilizando diferentes sistemas de análise

O presente estudo tem como objetivo comparar experimentalmente duas crianças praticantes de Hóquei em Patins, uma normal e uma com a patologia dos joelhos valgos, avaliando qualitativamente as diferenças posturais, estáticas e dinâmicas, decorrentes da utilização dos patins específicos desta modalidade, através do sistema de análise da Força de Reação do Solo (FRS), de Eletromiografia (EMG), de captura de movimento, e de modelação e simulação. Para atingir o objetivo definiu-se um protocolo de ensaios com as seguintes tarefas: repouso com e sem patins, marcha, corrida, deslizar com os dois pés apoiados e deslizar com o pé esquerdo levantado. No repouso avaliou-se a variação do ponto de aplicação da FRS da criança normal e patológica, com e sem patins. Ainda na tarefa de repouso avaliou-se também as componentes médio-lateral, antero-posterior individualmente e a componente vertical da FRS, juntamente com a atividade muscular dos músculos Gastrocnémio Medial (GM), Recto Femoral (RF), Vasto Medial (VM), Vasto Lateral (VL), Bicípete Femoral (BF), Semitendinoso (ST), Tensor da Fascia Lata (TFL), Gastrocnémio Lateral (GL), de forma a comparar os valores de intensidade de FRS e da atividade muscular dos diferentes instantes de tempo desta tarefa. Para as restantes tarefas apenas se avaliou individualmente as componentes médio-lateral e antero-posterior da FRS e a componente vertical da FRS juntamente com a atividade muscular dos referidos músculos, salientando as diferenças evidentes entre as curvas da criança normal e as curvas da criança patológica durante os diferentes instantes do movimento. Todas as tarefas referidas, exceto a tarefa de repouso com patins, foram ainda simuladas recorrendo a modelos músculo-esqueléticos. A partir destas simulações do movimento obtiveram-se os ângulos articulares e efetuou-se a respetiva análise. No final dos resultados obtidos apresentou-se uma tabela de resumo com o cálculo dos coeficientes de variação de cada grandeza, exceto nos gráficos da posição no espaço da FRS, onde se constatou que existe uma grande variabilidade inter-individuo em cada tarefa. A análise dos resultados de cada tarefa permite concluir que a utilização de patins pode trazer uma maior ativação muscular para a criança patológica, embora se verifique instabilidade articular. Apesar dessa instabilidade pode-se inferir que, uma maior ativação muscular decorrente da utilização de patins, tal como acontece na prática do hóquei em patins, pode trazer uma melhoria, a longo prazo, na estabilidade da articulação do joelho e na sustentação corporal, proporcionada pelo fortalecimento muscular.

Sistemas de avaliação de desempenho e gestão por objectivos: concepção, implementação e desenvolvimento

Trabalho de natureza profissional para a atribuição do Título de Especialista do Instituto Politécnico do Porto, na área de Recursos Humanos, defendido a 26-09-2012.

An integrated recycling approach for GFRP pultrusion wastes: recycling and reuse assessment into new composite materials using Fuzzy Boolean Nets

In this study, efforts were made in order to put forward an integrated recycling approach for the thermoset based glass fibre reinforced polymer (GPRP) rejects derived from the pultrusion manufacturing industry. Both the recycling process and the development of a new cost-effective end-use application for the recyclates were considered. For this purpose, i) among the several available recycling techniques for thermoset based composite materials, the most suitable one for the envisaged application was selected (mechanical recycling); and ii) an experimental work was carried out in order to assess the added-value of the obtained recyclates as aggregates and reinforcement replacements into concrete-polymer composite materials. Potential recycling solution was assessed by mechanical behaviour of resultant GFRP waste modified concrete-polymer composites with regard to unmodified materials. In the mix design process of the new GFRP waste based composite material, the recyclate content and size grade, and the effect of the incorporation of an adhesion promoter were considered as material factors and systematically tested between reasonable ranges. The optimization process of the modified formulations was supported by the Fuzzy Boolean Nets methodology, which allowed finding the best balance between material parameters that maximizes both flexural and compressive strengths of final composite. Comparing to related end-use applications of GFRP wastes in cementitious based concrete materials, the proposed solution overcome some of the problems found, namely the possible incompatibilities arisen from alkalis-silica reaction and the decrease in the mechanical properties due to high water-cement ratio required to achieve the desirable workability. Obtained results were very promising towards a global cost-effective waste management solution for GFRP industrial wastes and end-of-life products that will lead to a more sustainable composite materials industry.

F-LQE: a Fuzzy Link Quality Estimator for wireless sensor networks

Radio Link Quality Estimation (LQE) is a fundamental building block for Wireless Sensor Networks, namely for a reliable deployment, resource management and routing. Existing LQEs (e.g. PRR, ETX, Fourbit, and LQI ) are based on a single link property, thus leading to inaccurate estimation. In this paper, we propose F-LQE, that estimates link quality on the basis of four link quality properties: packet delivery, asymmetry, stability, and channel quality. Each of these properties is defined in linguistic terms, the natural language of Fuzzy Logic. The overall quality of the link is specified as a fuzzy rule whose evaluation returns the membership of the link in the fuzzy subset of good links. Values of the membership function are smoothed using EWMA filter to improve stability. An extensive experimental analysis shows that F-LQE outperforms existing estimators.

Fuzzy modelling of prescribed burning effects on soil physical properties

This paper presents the preliminary work of an approach where Fuzzy Boolean Nets (FBN) are being used to extract qualitative knowledge regarding the effect of prescribed fire burning on soil chemical physical properties. FBN were chosen due to the scarcity on available quantitative data.

Prescribed burning impact on forest soil properties – a fuzzy boolean nets approach

The Portuguese northern forests are often and severely affected by wildfires during the Summer season. These occurrences significantly affect and negatively impact all ecosystems, namely soil, fauna and flora. In order to reduce the occurrences of natural wildfires, some measures to control the availability of fuel mass are regularly implemented. Those preventive actions concern mainly prescribed burnings and vegetation pruning. This work reports on the impact of a prescribed burning on several forest soil properties, namely pH, soil moisture, organic matter content and iron content, by monitoring the soil self-recovery capabilities during a one year span. The experiments were carried out in soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, Portugal, which was kept intact from prescribed burnings during a period of four years. Soil samples were collected from five plots at three different layers (0–3, 3–6 and 6–18) 1 day before prescribed fire and at regular intervals after the prescribed fire. This paper presents an approach where Fuzzy Boolean Nets (FBN) and Fuzzy reasoning are used to extract qualitative knowledge regarding the effect of prescribed fire burning on soil properties. FBN were chosen due to the scarcity on available quantitative data. The results showed that soil properties were affected by prescribed burning practice and were unable to recover their initial values after one year.

Soluções globais de suporte aos sistemas de informação do século XXI

20 e 21 de novembro de 1998, Coimbra