Estrutura ANFIS modificada para identificação e controle de plantas com ampla faixa de operação e não linearidade acentuada

In this work a modification on ANFIS (Adaptive Network Based Fuzzy Inference System) structure is proposed to find a systematic method for nonlinear plants, with large operational range, identification and control, using linear local systems: models and controllers. This method is based on multiple model approach. This way, linear local models are obtained and then those models are combined by the proposed neurofuzzy structure. A metric that allows a satisfactory combination of those models is obtained after the structure training. It results on plant s global identification. A controller is projected for each local model. The global control is obtained by mixing local controllers signals. This is done by the modified ANFIS. The modification on ANFIS architecture allows the two neurofuzzy structures knowledge sharing. So the same metric obtained to combine models can be used to combine controllers. Two cases study are used to validate the new ANFIS structure. The knowledge sharing is evaluated in the second case study. It shows that just one modified ANFIS structure is necessary to combine linear models to identify, a nonlinear plant, and combine linear controllers to control this plant. The proposed method allows the usage of any identification and control techniques for local models and local controllers obtaining. It also reduces the complexity of ANFIS usage for identification and control. This work has prioritized simpler techniques for the identification and control systems to simplify the use of the method

Identificação não linear usando uma rede fuzzy wavelet neural network modificada

In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

Identificação de nematóides através de técnicas de processamento inteligentes de imagens

abstract

Identificação remota de sistemas operacionais utilizando análise de processos aleatórios e redes neurais artificiais

A new method to perform TCP/IP fingerprinting is proposed. TCP/IP fingerprinting is the process of identify a remote machine through a TCP/IP based computer network. This method has many applications related to network security. Both intrusion and defence procedures may use this process to achieve their objectives. There are many known methods that perform this process in favorable conditions. However, nowadays there are many adversities that reduce the identification performance. This work aims the creation of a new OS fingerprinting tool that bypass these actual problems. The proposed method is based on the use of attractors reconstruction and neural networks to characterize and classify pseudo-random numbers generators

Identificação de uma planta de corrente de um motor de indução utilizando redes de base radial

The present work describes the use of a mathematical tool to solve problems arising from control theory, including the identification, analysis of the phase portrait and stability, as well as the temporal evolution of the plant s current induction motor. The system identification is an area of mathematical modeling that has as its objective the study of techniques which can determine a dynamic model in representing a real system. The tool used in the identification and analysis of nonlinear dynamical system is the Radial Basis Function (RBF). The process or plant that is used has a mathematical model unknown, but belongs to a particular class that contains an internal dynamics that can be modeled.Will be presented as contributions to the analysis of asymptotic stability of the RBF. The identification using radial basis function is demonstrated through computer simulations from a real data set obtained from the plant

Identificação em tempo real de modelo dinâmico de robô móvel com acionamento diferencial e zona morta

Several mobile robots show non-linear behavior, mainly due friction phenomena between the mechanical parts of the robot or between the robot and the ground. Linear models are efficient in some cases, but it is necessary take the robot non-linearity in consideration when precise displacement and positioning are desired. In this work a parametric model identification procedure for a mobile robot with differential drive that considers the dead-zone in the robot actuators is proposed. The method consists in dividing the system into Hammerstein systems and then uses the key-term separation principle to present the input-output relations which shows the parameters from both linear and non-linear blocks. The parameters are then simultaneously estimated through a recursive least squares algorithm. The results shows that is possible to identify the dead-zone thresholds together with the linear parameters

Modelagem linear e identificação do modelo dinâmico de um robô móvel com acionamento diferencial

This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

Identificação Visual de Caixas de Medicamentos Usando Features Correspondentes

This work uses computer vision algorithms related to features in the identification of medicine boxes for the visually impaired. The system is for people who have a disease that compromises his vision, hindering the identification of the correct medicine to be ingested. We use the camera, available in several popular devices such as computers, televisions and phones, to identify the box of the correct medicine and audio through the image, showing the poor information about the medication, such: as the dosage, indication and contraindications of the medication. We utilize a model of object detection using algorithms to identify the features in the boxes of drugs and playing the audio at the time of detection of feauteres in those boxes. Experiments carried out with 15 people show that where 93 % think that the system is useful and very helpful in identifying drugs for boxes. So, it is necessary to make use of this technology to help several people with visual impairments to take the right medicine, at the time indicated in advance by the physician

Superando os riscos da segurança baseada em perímetro - Uma abordagem com identificação federada através de certificados digitais A3/ICP-Brasil e SAML

The traditional perimeter-based approach for computer network security (the castle and the moat model) hinders the progress of enterprise systems and promotes, both in administrators and users, the delusion that systems are protected. To deal with the new range of threats, a new data-safety oriented paradigm, called de-perimeterisation , began to be studied in the last decade. One of the requirements for the implementation of the de-perimeterised model of security is the definition of a safe and effective mechanism for federated identity. This work seeks to fill this gap by presenting the specification, modelling and implementation of a mechanism for federated identity, based on the combination of SAML and X.509 digital certificates stored in smart-cards, following the A3 standard of ICP-Brasil (Brazilian official certificate authority and PKI)

Identificação de modelos polinomiais narx utilizando algoritmos combinados de detecção de estrutura e estimação de parâmetros com aplicações práticas

A modelagem de processos industriais tem auxiliado na produção e minimização de custos, permitindo a previsão dos comportamentos futuros do sistema, supervisão de processos e projeto de controladores. Ao observar os benefícios proporcionados pela modelagem, objetiva-se primeiramente, nesta dissertação, apresentar uma metodologia de identificação de modelos não-lineares com estrutura NARX, a partir da implementação de algoritmos combinados de detecção de estrutura e estimação de parâmetros. Inicialmente, será ressaltada a importância da identificação de sistemas na otimização de processos industriais, especificamente a escolha do modelo para representar adequadamente as dinâmicas do sistema. Em seguida, será apresentada uma breve revisão das etapas que compõem a identificação de sistemas. Na sequência, serão apresentados os métodos fundamentais para detecção de estrutura (Modificado Gram- Schmidt) e estimação de parâmetros (Método dos Mínimos Quadrados e Método dos Mínimos Quadrados Estendido) de modelos. No trabalho será também realizada, através dos algoritmos implementados, a identificação de dois processos industriais distintos representados por uma planta de nível didática, que possibilita o controle de nível e vazão, e uma planta de processamento primário de petróleo simulada, que tem como objetivo representar um tratamento primário do petróleo que ocorre em plataformas petrolíferas. A dissertação é finalizada com uma avaliação dos desempenhos dos modelos obtidos, quando comparados com o sistema. A partir desta avaliação, será possível observar se os modelos identificados são capazes de representar as características estáticas e dinâmicas dos sistemas apresentados nesta dissertação

Identificação e caracterização de um isolado de Hydrangea ringspot virus em hortênsia no Estado de São Paulo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desenvolvimento de iniciadores para detecção e identificação de Diaporthe phaseolorum var. meridionalis em sementes de soja

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

Eletroforese de isoenzimas de plântulas na identificação de espécies de Brachiaria

Lotes de sementes de braquiária comercializados no Brasil vem apresentando contaminações com sementes de outras espécies pertencentes ao mesmo gênero. Deste modo, uma das espécies de braquiária atuaria como planta infestante da outra no agroecossistema e a erradicação da espécie infestante seria dificultada pela agressividade característica do gênero e pela falta de seletividade dos herbicidas disponíveis no mercado. Esses fatores ressaltam a importância da comercialização e utilização de lotes de sementes isento de sementes de outras espécies e a utilização de metodologias precisas de identificação das principais espécies de braquiária no controle de qualidade das empresas produtoras de sementes. Neste trabalho, buscou-se avaliar o potencial discriminante da técnica de eletroforese, utilizando quatro sistemas enzimáticos presentes em plântulas de quatro espécies do gênero Brachiaria, quer sejam B. brizantha cv. Marandu, B. decumbens cv. Basilisk, B. humidicola cv. comercial e B. plantaginea. Foram realizadas análises de eletroforese de isoenzimas testando-se 50 indivíduos de cada espécie por tratamento, utilizando-se coleóptilos de plântulas obtidas a partir de sementes germinadas a 30°C, no escuro. Para a eletroforese foi utilizado como meio suporte géis de poliacrilamida, nas concentrações de 7,0 e 7,5%. As isoenzimas Glutamato desidrogenase e Glucose-6-fosfato desidrogenase, embora eficientes na diferenciação entre B. plantaginea e B. humidicola e entre as sementes dessas espécies e as de B. brizantha ou B. decumbens, não se mostraram capazes de diferenciar as sementes destas duas últimas espécies. Entretanto, as izoenzimas α- e β-esterase possibilitaram uma nítida diferenciação das quatro espécies de Brachiaria estudadas.

Padronização da metodologia do RT-PCR utilizado para identificação do mRNA da alfa-amilase em sementes de milho

Durante a germinação das sementes, os carboidratos de reserva são degradados pela atividade de a-amilase. A identificação de mRNA é uma ferramenta fundamental para a definição da cinética de síntese de alfa-amilase. Objetivou-se padronizar a metodologia do RT-PCR para identificar o mRNA do gene de a-amilase em sementes de milho. Após três dias de germinação das cultivares Saracura-BRS 4154 e CATI-AL34, extraiu-se o RNA total pelo método do tiocianato de guanidina-fenol-clorofórmio, com algumas modificações. A partir do RNA total extraído foi obtido cDNA com utilização de random primers. A amplificação por PCR de uma porção do gene da alfa-amilase foi realizada com os primers: sense - CGACATCGACCACCTCAAC; antisense - TTGACCAGCTCCTGCCTGTC; gelatina; DMSO e 1,25 unidades de Taq DNA polimerase por reação e completados com água tratada com DEPC. Os ciclos para a amplificação foram 94ºC durante 4 minutos, seguidos por 34 ciclos de 94ºC durante 1 minuto, 42ºC durante 1 minuto e 72ºC durante 1,5 minutos e, finalmente, 72ºC por 5 minutos. O produto do RT-PCR apresentou uma banda de 249 pares de base (pb) bem definida, para as duas cultivares estudadas, não ocorrendo bandas inespecíficas. A técnica do RT-PCR mostrou ser uma metodologia eficiente para a identificação da expressão de alfa-amilase durante a germinação das sementes e pode ser usado para estudo qualitativo e quantitativo da cinética de síntese dessa enzima em experimentos de germinação.

Avaliação, identificação e atividade enzimática de bactérias psicotróficas presentes no leite cru refrigerado

Extended storage of refrigerated milk can lead to reduced quality of raw and processed milk, which is a consequence of the growth and metabolic activities of psychrotrophic bacteria, able to grow under 7oC or lower temperatures. Although most of these microorganisms are destroyed by heat treatment, some have the potential to produce termoresistant proteolytic and lipolytic enzymes that can survive even UHT processing and reduce the processed products quality. Recently, the IN 51 determineds that milk should be refrigerated and stored at the farm what increased the importance of this group of microorganisms. In this work, psychrotrophic bacteria were isolated from 20 communitarian bulk tanks and 23 individual bulk tanks from dairy farms located at Zona da Mata region of Minas Gerais State and from southeastern Rio de Janeiro. Selected milk dilutions were plated on standard agar and after incubation for 10 days at 7oC, five colonies were isolated, firstly using nutrient agar and after using McConkey agar for 24 hours at 21oC. The isolates were identified by morphology, Gram stain method, catalase production, fermentative/oxidative metabolism and by API 20E, API 20NE, API Staph, API Coryne or API 50 CH (BioMerieux). In order to ensure reproductibility, API was repeated for 50% of the isolates. Species identification was considered when APILAB indexes reached 75% or higher. 309 strains were isolated, 250 Gram negative and 59 Gram positive. 250 Gram negative isolates were identified as: Acinetobacter spp. (39), Aeromonas spp. (07), A. Hydrophila (16), A. sobria (1), A. caviae (1), Alcaligenes feacalis (1), Burkholderia cepacia (12), Chryseomonas luteola (3), Enterobacter sp. (1), Ewingella americana(6), Hafnia alvei (7), Klebsiella sp. (1), Klebsiella oxytoca (10), Yersinia spp. (2), Methylobacterium mesophilicum (1), Moraxella spp. (4), Pantoea spp. (16), Pasteurella sp. (1), Pseudomonas spp. (10), P. fluorescens (94), P. putida (3), Serratia spp. (3), Sphigomonas paucomobilis (1). Five isolates kept unidentified. Pseudomonas was the predominant bacteria found (43%) and P. fluorescens the predominant species (37.6%), in accordance with previous reports. Qualitative analysis of proteolytic and lipolytic activity was based on halo formation using caseinate agar and tributirina agar during 72 hours at 21oC and during 10 days at 4°C, 10oC and 7°C. Among 250 Gram negative bacteria found, 104 were identified as Pseudomonas spp. and 60,57% of this group showed proteolytic and lipolytic acitivities over all four studied temperatures. 20% of Acinetobacter, Aeromonas, Alcaligenes, Burkholderia, Chryseomonas, Methylobacterium, Moraxella presented only lipolytic activity. Some isolates presented enzymatic activity in one or more studied temperatures. Among Gram positive bacteria, 30.51% were proteolytic and lipolytic at 10oC, 8.47% were proteolytic at 7oC, 10oC, and 21oC, 8.47% were proteolytic at all studied temperatures (4oC, 7oC, 10oC and 21oC) and 3.38% were proteolytic only at 21oC. At 4oC, only one isolate showed proteolytic activity and six isolates were lipolytic. In relation to Gram negative microorganisms, 4% were proteolytic and lipolytic at 7oC, 10oC and 21oC, 10% were proteolytic at 10oC and 4.4% were lipolytic at 4oC, 7oC, 10oC and 21oC, while 6.4% of all isolates were proteolytic and lipolytic at 10oC and 21oC as well as lipolytic at 4oC and 7oC. These findings are in accordance with previous researches that pointed out Pseudomonas as the predominant psycrotrophic flora in stored refrigerated raw milk