Multivalued adaptive neuro-fuzzy controller for robot vehicle - art. no. 1406

Robotic vehicle navigation in unstructured and uncertain environments is still a challenge. This paper presents the implementation of a multivalued neurofuzzy controller for autonomous ground vehicle (AGVs) in indoor environments. The control system consists of a hierarchy of mobile robot using multivalued adaptive neuro-fuzzy inference system behaviors.

Sufficients conditions for analysis of extrema in the step-response of the linear control systems

This note deals whith the problem of extrema which may occur in the step-response of a stable linear system with real zeros and poles. Some simple sufficients conditions and necessary conditions are presented for analyses when zeros located between the dominant and fastest pole does not cause extrema in the step-response. These conditions require knowledge of the pole-zero configuration of the corresponding transfer-function.

Effect of a heat-treatment on the linear dimensional change of a hard chairside reline resin

Statement of problem. Little data are available regarding the effect of heat-treatments on the dimensional stability of hard chairside reline resins. Purpose. The objective of this in vitro study was to evaluate whether a heat-treatment improves the dimensional stability of the reline resin Duraliner II and to compare the linear dimensional changes of this material with the heat-polymerized acrylic resin Lucitone 550. Material and methods. The materials were mixed according to the manufacturer's instructions and packed into a stainless steel split mold (50.0 mm diameter and 0.5 mm thickness) with reference points (A, B, C, and D). Duraliner II specimens were polymerized for 12 minutes in water at 37°C and bench cooled to room temperature before being removed from the mold. Twelve specimens were made and divided into 2 groups: group 1 specimens (n=6) were left untreated, and group 2 specimens (n=6) were submitted to a heat-treatment in a water bath at 55°C for 10 minutes and then bench cooled to room temperature. The 6 Lucitone specimens (control group) were polymerized in a water bath for 9 hours at 71°C. The specimens were removed after the mold reached the room temperature. A Nikon optical comparator was used to measure the distances between the reference points (AB and CD) on the stainless steel mold (baseline readings) and on the specimens to the nearest 0.001 mm. Measurements were made after processing and after the specimens had been stored in distilled water at 37°C for 8 different periods of time. Data were subjected to analysis of variance with repeated measures, followed by Tukey's multiple comparison test (P<.05). Results. All specimens exhibited shrinkage after processing (control, -0.41%; group 1, -0.26%; and group 2, -0.51%). Group 1 specimens showed greater shrinkage (-1.23%) than the control (-0.23%) and group 2 (-0.81%) specimens after 60 days of storage in water (P<.05). Conclusion. Within the limitations of this study, a significant improvement of the long-term dimensional stability of the Duraliner II reline resin was observed when the specimens were heat-treated. However, the shrinkage remained considerably higher than the denture base resin Lucitone 550. Copyright © 2002 by The Editorial Council of The Journal of Prosthetic Dentistry.

Tuning of fuzzy inference systems through unconstrained optimization techniques

This paper presents a new methodology for the adjustment of fuzzy inference systems. A novel approach, which uses unconstrained optimization techniques, is developed in order to adjust the free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through an estimation of time series. More specifically, the Mackey-Glass chaotic time series estimation is used for the validation of the proposed methodology.

A multiagent architecture for supervisory and control system

Supervising and controlling the many processes involved in petroleum production is both dangerous and complex. Herein, we propose a multiagent supervisory and control system for handle continuous processes like those in chemical and petroleum industries In its architeture, there are agents responsible for managing data production and analysis, and also the production equipments. Fuzzy controllers were used as control agents. The application of a fuzzy control system to managing an off-shore installation for petroleum production onto a submarine separation process is described. © 2008 IEEE.

Development of a water quality index using a fuzzy logic: A case study for the sorocaba river

Due to growing urbanization and industrialization, the environment is suffering from pollution of rivers, degradation of soils and deteriorated air quality. Quality indices appear to be useful to evaluate the conditions of these media. The aim of this study was the development of a water quality index using a fuzzy inference system, since such an approach has proved advantageous in addressing problems that are subjective by nature or for which the data are uncertain. The methodology employed was based on this inference system, and considered the nine water quality parameters employed by CETESB (Companhia de Tecnologia de Saneamento Ambiental, São Paulo, Brazil) to evaluate water quality. After assessment of the data using the index, a comparison was made with the WQI (Water Quality Index), which is used for the monitoring of various water bodies, including in the study region. The results obtained using the index developed on the basis of fuzzy inference were found to be more useful than those derived from the method currently used by CETESB, since losses and/or omissions concerning individual parameters were minimized. © 2010 IEEE.

Análise da estabilidade de sistemas fuzzy Takagi-Sugeno utilizando as desigualdades de Lyapunov-Metzler

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparison between the performances of a linear isolator and an isolator with a geometrically nonlinear damper

Pós-graduação em Engenharia Mecânica - FEIS

Controle automático de adição de AlF3 em cubas de redução de alumínio, usando lógica fuzzy

Este trabalho descreve um sistema de análise de dados com a finalidade de gerar um sistema de controle utilizando técnica inteligente para adição de fluoreto de alumínio (AlF3) em fornos de redução de alumínio. O projeto baseia-se nos conceitos de lógica fuzzy, nos quais o conhecimento acumulado pelo especialista do processo é traduzido de maneira qualitativa em um conjunto de regras linguísticas do tipo SE ENTÃO. A utilização desta técnica inteligente para o controle de adição de fluoreto busca representar explicitamente um conhecimento qualitativo, detido pelos operadores de cubas eletrolíticas. Devido o sistema convencional não contemplar as variações dos fenômenos que envolvem a dinâmica do processo, um controlador fuzzy foi implmentado no sistema real para tomadas de decisões, utilizando o modelo mínimo de Mandani. Baseado neste modelo, as variáveis de processo para a entrada do sistema fuzzy, tais como temperatura de banho e percentual de fluoreto foram manipuladas para estimar a tendência de subida e descida, respectivamente, através do método mínimos quadrados(MMQ). O controlador fuzzy é aplicado para calcular a quantidade de fluoreto de alumínio (AlF3) a ser adicionado na cuba eletrolítica de forma automática sem a necessidade da intervenção do especialista do processo. A motivação para o uso de um sistema de controle fuzzy se deve ao fato de não se ter disponível um modelo dinâmico do processo de adição do fluoreto na cuba eletrolítica. Esta falta de modelagem se deve ao fato de grande complexidade dos fenômenos envolvidos em uma cuba que são processos termodinâmicos e eletromagnéticos acoplados.

Metodologia para diagnosticar a qualidade de energia elétrica referente à distorção harmônica em sistema trifásico de baixa tensão utilizando lógica fuzzy

Este trabalho ressalta a importância de monitorar e diagnosticar a qualidade de energia elétrica sob a ótica das distorções harmônicas presente nas instalações elétricas em sistema trifásico de baixa tensão através de uma proposta metodológica para analisar e diagnosticar o nível dos distúrbios harmônico avaliando o indicador total de distorção harmônica (THD), apoiado por um sistema especialista baseado em um sistema de inferência Fuzzy.

Aumento da produtividade: utilizando a metodologia Six Sigma e Lógica Fuzzy, um estudo de caso em uma empresa do Pólo Industrial de Manaus – PIM

Este trabalho utiliza a metodologia six sigma com o objetivo de aumentar a produtividade da Linha de LCD (Liquid Crystal Display) em uma fábrica do Pólo Industrial de Manaus - PIM e um sistema de inferência fuzzy para mensurar o aumento dessa produtividade, onde foram identificados vários parâmetros baseados na metodologia six sigma. Dentre os quais, conforme grau de relevância dos especialistas deste estudo, pode-se destacar: desperdícios, capacidade produtiva e estudo de tempos. Ressaltando ainda que o sistema proposto seja de grande importância para profissionais e pesquisadores da gestão da produção, os quais desejam resultados que reduzam custos e conseqüentemente aumente os lucros da organização.

Desenvolvimento de aplicações em medicina e agronomia utilizando lógica fuzzy e neuro fuzzy

Pós-graduação em Engenharia Elétrica - FEIS

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.

Vibration Control Applied in a Semi-Active Suspension using Magneto Rheological Damper and Optimal Linear Control Design

In this paper we study the behavior of a semi-active suspension witch external vibrations. The mathematical model is proposed coupled to a magneto rheological (MR) damper. The goal of this work is stabilize of the external vibration that affect the comfort and durability an vehicle, to control these vibrations we propose the combination of two control strategies, the optimal linear control and the magneto rheological (MR) damper. The optimal linear control is a linear feedback control problem for nonlinear systems, under the optimal control theory viewpoint We also developed the optimal linear control design with the scope in to reducing the external vibrating of the nonlinear systems in a stable point. Here, we discuss the conditions that allow us to the linear optimal control for this kind of non-linear system.

Bifurcations Leading to Nonlinear Oscillations in a 3D Piecewise Linear Memristor Oscillator

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