Control of Limit Cycle Oscillation in a Three Degrees of Freedom Airfoil Section Using Fuzzy Takagi-Sugeno Modeling

This work presents a strategy to control nonlinear responses of aeroelastic systems with control surface freeplay. The proposed methodology is developed for the three degrees of freedom typical section airfoil considering aerodynamic forces from Theodorsen's theory. The mathematical model is written in the state space representation using rational function approximation to write the aerodynamic forces in time domain. The control system is designed using the fuzzy Takagi-Sugeno modeling to compute a feedback control gain. It useds Lyapunov's stability function and linear matrix inequalities (LMIs) to solve a convex optimization problem. Time simulations with different initial conditions are performed using a modified Runge-Kutta algorithm to compare the system with and without control forces. It is shown that this approach can compute linear control gain able to stabilize aeroelastic systems with discontinuous nonlinearities.

Estimativa da produtividade de trigo em função da adubação nitrogenada utilizando modelagem neuro fuzzy

Currently new techniques for data processing, such as neural networks, fuzzy logic and hybrid systems are used to develop predictive models of complex systems and to estimate the desired parameters. In this article the use of an adaptive neuro fuzzy inference system was investigated to estimate the productivity of wheat, using a database of combination of the following treatments: five N doses (0, 50, 100, 150 and 200 kg ha(-1)), three sources (Entec, ammonium sulfate and urea), two application times of N (at sowing or at side-dressing) and two wheat cultivars (IAC 370 and E21), that were evaluated during two years in Selviria, Mato Grosso do Sul, Brazil. Through the input and output data, the system of adaptive neuro fuzzy inference learns, and then can estimate a new value of wheat yield with different N doses. The productivity prediciton error of wheat in function of five N doses, using a neuro fuzzy system, was smaller than that one obtained with a quadratic approximation. The results show that the neuro fuzzy system is a viable prediction model for estimating the wheat yield in function of N doses.

Defining functional urban regions in Bahia, Brazil, using roadway coverage and population density variables

The concept of Functional Urban Regions (FURs), also called Metropolitan Regions (MRs), is not simple. It is clear, though, that they are not simply a combination of adjacent municipalities or areas. Different methods can be used for their definition. However, especially in developing countries, the application of some methods is not possible, due to the unavailability of detailed data. Alternative approaches have been developed based on spatial analysis methods and using variables extracted from available data. The objective of this study is to compare the results of two spatial analysis methods exploring two variables: population density and an indicator of transport infrastructure supply. The first method regards Exploratory Spatial Data Analyses tools, which define uniform regions based on specific variables. The second method used the same variables and the spatial analysis technique available in the computer program SKATER - Spatial 'K'luster Analysis by Tree Edge Removal. Assuming that those classifications of regions with similar characteristics can be used for identifying potential FURS, the results of all analyses were compared with one another and with the 'official' MR. A combined approach was also considered for comparison, but none of the results match the existing MR boundaries, what challenges the official definitions. (C) 2014 Elsevier Ltd. All rights reserved.

Robust Switched Control Design for Nonlinear Systems Using Fuzzy Models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aplicação de lógica fuzzy na elaboração de planta de valores genéricos

Pós-graduação em Ciências Cartográficas - FCT

Estimating the average length of hospitalization due to pneumonia: a fuzzy approach

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimating outcomes in newborn infants using fuzzy logic

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Lógica Fuzzy Aplicada à Recuperação de Informação

The information retrieval process involves subjective, imprecise and vague concepts, such as "information need", "relevance", and the very concept of "information". The main information retrieval models treat these concepts accurately, represented by a single numerical value. The fuzzy logic, while operating with the uncertainty of natural phenomena in a systematic and rigorous manner, represents a promising alternative to solve some problems related to information retrieval. This paper presents the fuzzy logic and some examples of its use in information retrieval systems (IRS).

A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill

This paper proposes a Fuzzy Goal Programming model (FGP) for a real aggregate production-planning problem. To do so, an application was made in a Brazilian Sugar and Ethanol Milling Company. The FGP Model depicts the comprehensive production process of sugar, ethanol, molasses and derivatives, and considers the uncertainties involved in ethanol and sugar production. Decision-makings, related to the agricultural and logistics phases, were considered on a weekly-basis planning horizon to include the whole harvesting season and the periods between harvests. The research has provided interesting results about decisions in the agricultural stages of cutting, loading and transportation to sugarcane suppliers and, especially, in milling decisions, whose choice of production process includes storage and logistics distribution. (C)2014 Elsevier B.V. All rights reserved.

An improved interolog mapping-based computational prediction of protein protein interactions with increased network coverage

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

On Switched Regulator Design of Uncertain Nonlinear Systems Using Takagi-Sugeno Fuzzy Models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Epidemiological Models of Directly Transmitted Diseases: An Approach via Fuzzy Sets Theory

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Analysis of Structural Integrity Using an ARTMAP-Fuzzy Artificial Neural Network

This paper presents the application of artificial neural networks in the analysis of the structural integrity of a building. The main objective is to apply an artificial neural network based on adaptive resonance theory, called ARTMAP-Fuzzy neural network and apply it to the identification and characterization of structural failure. This methodology can help professionals in the inspection of structures, to identify and characterize flaws in order to conduct preventative maintenance to ensure the integrity of the structure and decision-making. In order to validate the methodology was modeled a building of two walk, and from this model were simulated various situations (base-line condition and improper conditions), resulting in a database of signs, which were used as input data for ARTMAP-Fuzzy network. The results show efficiency, robustness and accuracy.

Simulação e controle de um quadcopter utilizando lógica fuzzy

The present work develops a model to simulate the dynamics of a quadcopter being controlled by a PD fuzzy controller. Initially is presented a brief history of quadcopters an introduction to fuzzy logic and fuzzy control systems. Afterwards is presented an overview of the quadcopter dynamics and the mathematical modelling development applying Newton-Euler method. Then the modelling are implemented in a Simulink model in addition to a PD fuzzy controller. A prototype proposition is made, by describing each necessary component to build up a quadcopter. In the end the results from the simulators are discussed and compared due to the discrepancy between the model using ideal sensor and the model using non-ideal sensors

Auxílio a tomada de decisão na inclusão de sobressalentes de manutenção em estoque utilizando um sistema especialista fuzzy

In the current economic scenario of constant changes, industries seek to increase their profitability decreasing inventory levels. Maintenance and maintenance management, combined with the inventory management of spare parts, has assumed a position of competitive advantage in business. Stock only what you need has become a difficult decision for managers, who are faced with the lack of models and criteria to assist this decision-making. This work proposes a method which supports decision making, on a MATLAB modeling, using criteria established by an expert and his maintenance workers team, focusing on no regular demand of spare parts. The proposed model was adequate to the needs of the company and the maintenance manager in the decision on the storage