Controle fuzzy espacialmente diferenciado para um sistema de irrigação

Traditional irrigation projects do not locally determine the water availability in the soil. Then, irregular irrigation cycles may occur: some with insufficient amount that leads to water deficit, other with excessive watering that causes lack of oxygen in plants. Due to the nonlinear nature of this problem and the multivariable context of irrigation processes, fuzzy logic is suggested to replace commercial ON-OFF irrigation system with predefined timing. Other limitation of commercial solutions is that irrigation processes either consider the different watering needs throughout plant growth cycles or the climate changes. In order to fulfill location based agricultural needs, it is indicated to monitor environmental data using wireless sensors connected to an intelligent control system. This is more evident in applications as precision agriculture. This work presents the theoretical and experimental development of a fuzzy system to implement a spatially differentiated control of an irrigation system, based on soil moisture measurement with wireless sensor nodes. The control system architecture is modular: a fuzzy supervisor determines the soil moisture set point of each sensor node area (according to the soil-plant set) and another fuzzy system, embedded in the sensor node, does the local control and actuates in the irrigation system. The fuzzy control system was simulated with SIMULINK® programming tool and was experimentally built embedded in mobile device SunSPOTTM operating in ZigBee. Controller models were designed and evaluated in different combinations of input variables and inference rules base

Obtenção dos parâmetros-x de estruturas planares

Due to major progress of communication system in the last decades, need for more precise characterization of used components. The S-parameters modeling has been used to characterization, simulation and test of communication system. However, limitation of S-parameters to model nonlinear system has created new modeling systems that include the nonlinear characteristics. The polyharmonic distortion modeling is a characterizationg technique for nonlinear systems that has been growing up due to praticity and similarity with S-parameters. This work presents analysis the polyharmonic distortion modeling, the test bench development for simulation of planar structure and planar structure characterization with X-parameters

Dimensionamento de sistemas de aterramento em linhas de transmissão para escoamento eficiente de correntes de surtos atmosféricos

This work presents in a simulated environment, to analyze the length of cable needed counterweight connected to ground rod, able to avoid the phenomenon of flashover return, back flashover, the insulator chains of transmission lines consisting of concrete structures when they are subjected to lightning standardized regarding certain resistivity values of some kinds of soil and geometric arrangements of disposal of grounding systems structures

Predição da incrustação em um trocador de calor baseada em redes neurais artificiais

A serious problem that affects an oil refinery s processing units is the deposition of solid particles or the fouling on the equipments. These residues are naturally present on the oil or are by-products of chemical reactions during its transport. A fouled heat exchanger loses its capacity to adequately heat the oil, needing to be shut down periodically for cleaning. Previous knowledge of the best period to shut down the exchanger may improve the energetic and production efficiency of the plant. In this work we develop a system to predict the fouling on a heat exchanger from the Potiguar Clara Camarão Refinery, based on data collected in a partnership with Petrobras. Recurrent Neural Networks are used to predict the heat exchanger s flow in future time. This variable is the main indicator of fouling, because its value decreases gradually as the deposits on the tubes reduce their diameter. The prediction could be used to tell when the flow will have decreased under an acceptable value, indicating when the exchanger shutdown for cleaning will be needed

Análise de escalabilidade de uma implementação paralela do simulated annealing acoplado

This paper analyzes the performance of a parallel implementation of Coupled Simulated Annealing (CSA) for the unconstrained optimization of continuous variables problems. Parallel processing is an efficient form of information processing with emphasis on exploration of simultaneous events in the execution of software. It arises primarily due to high computational performance demands, and the difficulty in increasing the speed of a single processing core. Despite multicore processors being easily found nowadays, several algorithms are not yet suitable for running on parallel architectures. The algorithm is characterized by a group of Simulated Annealing (SA) optimizers working together on refining the solution. Each SA optimizer runs on a single thread executed by different processors. In the analysis of parallel performance and scalability, these metrics were investigated: the execution time; the speedup of the algorithm with respect to increasing the number of processors; and the efficient use of processing elements with respect to the increasing size of the treated problem. Furthermore, the quality of the final solution was verified. For the study, this paper proposes a parallel version of CSA and its equivalent serial version. Both algorithms were analysed on 14 benchmark functions. For each of these functions, the CSA is evaluated using 2-24 optimizers. The results obtained are shown and discussed observing the analysis of the metrics. The conclusions of the paper characterize the CSA as a good parallel algorithm, both in the quality of the solutions and the parallel scalability and parallel efficiency

Algoritmos genéticos aplicados a um comitê de LS-SVM em problemas de classificação

The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers

Acelerando algoritmos de baixo nível em visão robótica com hardware reconfigurável

A challenge that remains in the robotics field is how to make a robot to react in real time to visual stimulus. Traditional computer vision algorithms used to overcome this problem are still very expensive taking too long when using common computer processors. Very simple algorithms like image filtering or even mathematical morphology operations may take too long. Researchers have implemented image processing algorithms in high parallelism hardware devices in order to cut down the time spent in the algorithms processing, with good results. By using hardware implemented image processing techniques and a platform oriented system that uses the Nios II Processor we propose an approach that uses the hardware processing and event based programming to simplify the vision based systems while at the same time accelerating some parts of the used algorithms

Estabilizador de sistema de potência para máquinas síncronas de polos salientes utilizando a transformada Wavelet

The power system stabilizers are used to suppress low-frequency electromechanical oscillations and improve the synchronous generator stability limits. This master thesis proposes a wavelet-based power system stabilizer, composed of a new methodology for extraction and compensation of electromechanical oscillations in electrical power systems based on the scaling coefficient energy of the maximal overlap discrete wavelet transform in order to reduce the effects of delay and attenuation of conventional power system stabilizers. Moreover, the wavelet coefficient energy is used for electric oscillation detection and triggering the power system stabilizer only in fault situations. The performance of the proposed power system stabilizer was assessed with experimental results and comparison with the conventional power system stabilizer. Furthermore, the effects of the mother wavelet were also evaluated in this work

Controle vetorial para velocidade de um motor de indução trifásico utilizando estimador filtro de Kalman

This paper describes the study, computer simulation and feasibility of implementation of vector control speed of an induction motor using for this purpose the Extended Kalman Filter as an estimator of rotor flux. The motivation for such work is the use of a control system that requires no sensors on the machine shaft, thus providing a considerable cost reduction of drives and their maintenance, increased reliability, robustness and noise immunity as compared to control systems with conventional sensors

Desenvolvimento de uma cadeira de rodas robótica para transporte de portador de necessidades especiais

The objective of the dissertation was the realization of kinematic modeling of a robotic wheelchair using virtual chains, allowing the wheelchair modeling as a set of robotic manipulator arms forming a cooperative parallel kinematic chain. This document presents the development of a robotic wheelchair to transport people with special needs who overcomes obstacles like a street curb and barriers to accessibility in streets and avenues, including the study of assistive technology, parallel architecture, kinematics modeling, construction and assembly of the prototype robot with the completion of a checklist of problems and barriers to accessibility in several pathways, based on rules, ordinances and existing laws. As a result, simulations were performed on the chair in various states of operation to accomplish the task of going up and down stair with different measures, making the proportional control based on kinematics. To verify the simulated results we developed a prototype robotic wheelchair. This project was developed to provide a better quality of life for people with disabilities

Uma proposta de metodologia para o ensino de Física usando robótica de baixíssimo custo

This paper presents methodology based on Lev Vigotsky`s social interactionist theory through investigative activities, which integrates the teaching of physics to robotics, directed to students of the Physics degree course, seeking to provide further training for future teachers. The method is organized through educational robotics workshops that addresses concepts of physics through the use of low-cost educational robots along with several activities. The methodology has been presented and discussed and put into practice afterwards in workshops so that these future teachers may be able to take robotics to their classroom. Students from the last and penultimate semester of the Physics degree course of the Federal Institute of Education, Science and Technology of Rio Grande do Norte, Caicó campus participated in this project

Controle de posição de uma plataforma plana para captação de radiação solar

This study aims at the design, development and performance evaluation of a flat platform to capture incident solar radiation. The design and implementation of a fuzzy system for the efficient control of the solar tracking movement of the platform are also presented

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

Caracterização de circuitos planares de micro-ondas pelo método iterativo das ondas

The planar circuits are structures that increasingly attracting the attention of researchers, due the good performance and capacity to integrate with other devices, in the prototyping of systems for transmitting and receiving signals in the microwave range. In this context, the study and development of new techniques for analysis of these devices have significantly contributed in the design of structures with excellent performance and high reliability. In this work, the full-wave method based on the concept of electromagnetic waves and the principle of reflection and transmission of waves at an interface, Wave Concept Iterative Procedure (WCIP), or iterative method of waves is described as a tool with high precision study microwave planar circuits. The proposed method is applied to the characterization of planar filters, microstrip antennas and frequency selective surfaces. Prototype devices were built and the experimental results confirmed the proposed mathematical model. The results were also compared with simulated results by Ansoft HFSS, observing a good agreement between them.

Controlador adaptativo por posicionamento de pólos e estrutura variável aplicado ao controle de geradores eólicos baseados em máquina de indução duplamente alimentada

In the last decade, the renewable energy sources have present a major propulsion in the world due to several factors: political, environmental, financial and others. Within this context, we have in particular the energy obtained through wind, wind energy - that has highlighted with rapid growth in recent years, including in Brazil, mostly in the Northeast, due to it s benefit-cost between the clean energies. In this context, we propose to compare the variable structure adaptive pole placement control (VS-APPC) with a traditional control technique proportional integral controller (PI), applied to set the control of machine side in a conversion system using a wind generator based on Double-Fed Induction Generator (DFIG). Robustness and performance tests were carried out to the uncertainties of the internal parameters of the machine and variations of speed reference.