Identificação e comparação entre controle preditivo com modelo não linear e PI sintonizados com PSO em sistema de separação gravitacional de águia-óleo

The separation methods are reduced applications as a result of the operational costs, the low output and the long time to separate the uids. But, these treatment methods are important because of the need for extraction of unwanted contaminants in the oil production. The water and the concentration of oil in water should be minimal (around 40 to 20 ppm) in order to take it to the sea. Because of the need of primary treatment, the objective of this project is to study and implement algorithms for identification of polynomial NARX (Nonlinear Auto-Regressive with Exogenous Input) models in closed loop, implement a structural identification, and compare strategies using PI control and updated on-line NARX predictive models on a combination of three-phase separator in series with three hydro cyclones batteries. The main goal of this project is to: obtain an optimized process of phase separation that will regulate the system, even in the presence of oil gushes; Show that it is possible to get optimized tunings for controllers analyzing the mesh as a whole, and evaluate and compare the strategies of PI and predictive control applied to the process. To accomplish these goals a simulator was used to represent the three phase separator and hydro cyclones. Algorithms were developed for system identification (NARX) using RLS(Recursive Least Square), along with methods for structure models detection. Predictive Control Algorithms were also implemented with NARX model updated on-line, and optimization algorithms using PSO (Particle Swarm Optimization). This project ends with a comparison of results obtained from the use of PI and predictive controllers (both with optimal state through the algorithm of cloud particles) in the simulated system. Thus, concluding that the performed optimizations make the system less sensitive to external perturbations and when optimized, the two controllers show similar results with the assessment of predictive control somewhat less sensitive to disturbances

Contribuições a técnicas de agrupamento e visualização de dados multivariados utilizando mapas auto-organizáveis

Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature

Modelos auto-similares para rádio fontes extragalácticas.

This work is a detailed study of self-similar models for the expansion of extragalactic radio sources. A review is made of the definitions of AGN, the unified model is discussed and the main characteristics of double radio sources are examined. Three classification schemes are outlined and the self-similar models found in the literature are studied in detail. A self-similar model is proposed that represents a generalization of the models found in the literature. In this model, the area of the head of the jet varies with the size of the jet with a power law with an exponent γ. The atmosphere has a variable density that may or may not be spherically symmetric and it is taken into account the time variation of the cinematic luminosity of the jet according to a power law with an exponent h. It is possible to show that models Type I, II and III are particular cases of the general model and one also discusses the evolution of the sources radio luminosity. One compares the evolutionary curves of the general model with the particular cases and with the observational data in a P-D diagram. The results show that the model allows a better agreement with the observations depending on the appropriate choice of the model parameters.

Influência da auto seleção à luz no ritmo circadiano de atividade motora em Callithrix Jacchus

Marmosets, Callithrix jacchus, are strictly diurnal animals. The motor activity rhythmicity is generated by the circadian timing system and is modulated by environmental factors, mainly by photic stimuli that compose the light-dark cycle. Photic stimuli can reset the biological oscilators changing activity motor pattern, by a mechanism called entrainment. Otherwise, light can act directly on expressed rhythm, without act on the biological oscillators, promoting the masking. Thus, photic stimuli can synchronize the circadian activity rhythm (CAR) by two distinct mechanisms, acting isolated or at a combined way. Among the elements that can influence photic synchronization, the duration and time of photic exposure is pointed out. If in the natural environment the marmoset can choose places of different intensity illumination and is synchronized to light-dark cycle (LD), how the photic synchronization mechanism can be evaluated in laboratory by light self-selection? With objective to response this question, four adult male marmosets were studied at two conditions: with and without sleeping box. The animals were submitted to a LD cycle (12:12/ 350:2 lx) and constant light (LL: 350 lx) conditions in individual cages with an opaque sleeping box, that permitted the light self-selection. At the room, the temperature was 25.6 ºC (± 0.3 ºC) and humidity was 78.7 (± 5%). The motor activity was recorded at 5 min bins by infrared movement sensors installed at the top of the cages. The motor activity profile was distinct at the two conditions: without the sleeping box protection against light, the activity frequency was higher at CT 11-12 (ANOVA; F(3.23) = 62.27; p < 0.01). Also, the duration of the active phase (α) was prolonged of about 1 h (t test, p < 0.05) and the animals showed a significant delay on the activity onset and offset (t test, p < 0.05) and at the acrophase (confidence intervals of 5%) of CAR. In LL, the light continuous exposure prolonged the active phase and influenced the endogenous expression of the circadian activity rhythm period. From the result analysis, it is concluded that the light self-selection can modify several parameters of CAR in marmosets, allowing the study of the synchronization mechanism using the burrow model. Thus, without sleeping box there was a phase delay between the CAR and LD (entrainment) and an increase of activity near lights off (positive masking). Furthermore, in LL, the light continuous exposure modifies α and the endogenous expression of CAR. It is suggested that the light self-selection might be take into account at investigations that evaluate the biological rhythmicity in marmosets

Uma abordagem dirigida por modelos para desenvolvimento de middlewares auto-adaptativos para transmissão de fluxo de dados baseado em restrições de QoS

The use of middleware technology in various types of systems, in order to abstract low-level details related to the distribution of application logic, is increasingly common. Among several systems that can be benefited from using these components, we highlight the distributed systems, where it is necessary to allow communications between software components located on different physical machines. An important issue related to the communication between distributed components is the provision of mechanisms for managing the quality of service. This work presents a metamodel for modeling middlewares based on components in order to provide to an application the abstraction of a communication between components involved in a data stream, regardless their location. Another feature of the metamodel is the possibility of self-adaptation related to the communication mechanism, either by updating the values of its configuration parameters, or by its replacement by another mechanism, in case of the restrictions of quality of service specified are not being guaranteed. In this respect, it is planned the monitoring of the communication state (application of techniques like feedback control loop), analyzing performance metrics related. The paradigm of Model Driven Development was used to generate the implementation of a middleware that will serve as proof of concept of the metamodel, and the configuration and reconfiguration policies related to the dynamic adaptation processes. In this sense was defined the metamodel associated to the process of a communication configuration. The MDD application also corresponds to the definition of the following transformations: the architectural model of the middleware in Java code, and the configuration model to XML