Arquitetura inteligente fuzzy para monitoramento de sinais vitais de pacientes: um estudo de caso em UTI

The area of the hospital automation has been the subject a lot of research, addressing relevant issues which can be automated, such as: management and control (electronic medical records, scheduling appointments, hospitalization, among others); communication (tracking patients, staff and materials), development of medical, hospital and laboratory equipment; monitoring (patients, staff and materials); and aid to medical diagnosis (according to each speciality). This thesis presents an architecture for a patient monitoring and alert systems. This architecture is based on intelligent systems techniques and is applied in hospital automation, specifically in the Intensive Care Unit (ICU) for the patient monitoring in hospital environment. The main goal of this architecture is to transform the multiparameter monitor data into useful information, through the knowledge of specialists and normal parameters of vital signs based on fuzzy logic that allows to extract information about the clinical condition of ICU patients and give a pre-diagnosis. Finally, alerts are dispatched to medical professionals in case any abnormality is found during monitoring. After the validation of the architecture, the fuzzy logic inferences were applied to the trainning and validation of an Artificial Neural Network for classification of the cases that were validated a priori with the fuzzy system

Arquitetura de controladores fuzzy em redes foundation fieldbus

Foundation Fieldbus Industrial networks are the high standard technology which allows users to create complex control logic and totally decentralized. Although being so advanced, they still have some limitations imposed by their own technology. Attempting to solve one of these limitations, this paper describes how to design a Fuzzy controller in a Foundation Fieldbus network using their basic elements of programming, the functional blocks, so that the network remains fully independent of other devices other than the same instruments that constitute it. Moreover, in this work was developed a tool that aids this process of building the Fuzzy controller, setting the internal parameters of functional blocks and informing how many and which blocks should be used for a given structure. The biggest challenge in creating this controller is exactly the choice of blocks and how to arrange them in order to effectuate the same functions of a Fuzzy controller implemented in other kind of environment. The methodology adopted was to divide each one of the phases of a traditional Fuzzy controller and then create simple structures with the functional blocks to implement them. At the end of the work, the developed controller is compared with a Fuzzy controller implemented in a mathematical program that it has a proper tool for the development and implementation of Fuzzy controllers, obtaining comparatives graphics of performance between both

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

On relaxed LMI-based design for fuzzy controllers

Relaxed conditions for stability of nonlinear continuous-time systems given by fuzzy models axe presented. A theoretical analysis shows that the proposed method provides better or at least the same results of the methods presented in the literature. Digital simulations exemplify this fact. This result is also used for fuzzy regulators design. The nonlinear systems are represented by fuzzy models proposed by Takagi and Sugeno. The stability analysis and the design of controllers axe described by LMIs (Linear Matrix Inequalities), that can be solved efficiently using convex programming techniques.

On relaxed LMI-based designs for fuzzy regulators and fuzzy observers

Relaxed conditions for stability of nonlinear, continuous and discrete-time systems given by fuzzy models are presented. A theoretical analysis shows that the proposed methods provide better or at least the same results of the methods presented in the literature. Numerical results exemplify this fact. These results are also used for fuzzy regulators and observers designs. The nonlinear systems are represented by fuzzy models proposed by Takagi and Sugeno. The stability analysis and the design of controllers are described by linear matrix inequalities, that can be solved efficiently using convex programming techniques. The specification of the decay rate, constrains on control input and output are also discussed.

Design of fuzzy regulators with optimal initial conditions compensation

In almost all cases, the goal of the design of automatic control systems is to obtain the parameters of the controllers, which are described by differential equations. In general, the controller is artificially built and it is possible to update its initial conditions. In the design of optimal quadratic regulators, the initial conditions of the controller can be changed in an optimal way and they can improve the performance of the controlled system. Following this idea, a LNU-based design procedure to update the initial conditions of PI controllers, considering the nonlinear plant described by Takagi-Sugeno fuzzy models, is presented. The importance of the proposed method is that it also allows other specifications, such as, the decay rate and constraints on control input and output. The application in the control of an inverted pendulum illustrates the effectively of proposed method.

Uma nova forma de calcular os centros dos Clusters em algoritmos de agrupamento tipo fuzzy c-means

Clustering data is a very important task in data mining, image processing and pattern recognition problems. One of the most popular clustering algorithms is the Fuzzy C-Means (FCM). This thesis proposes to implement a new way of calculating the cluster centers in the procedure of FCM algorithm which are called ckMeans, and in some variants of FCM, in particular, here we apply it for those variants that use other distances. The goal of this change is to reduce the number of iterations and processing time of these algorithms without affecting the quality of the partition, or even to improve the number of correct classifications in some cases. Also, we developed an algorithm based on ckMeans to manipulate interval data considering interval membership degrees. This algorithm allows the representation of data without converting interval data into punctual ones, as it happens to other extensions of FCM that deal with interval data. In order to validate the proposed methodologies it was made a comparison between a clustering for ckMeans, K-Means and FCM algorithms (since the algorithm proposed in this paper to calculate the centers is similar to the K-Means) considering three different distances. We used several known databases. In this case, the results of Interval ckMeans were compared with the results of other clustering algorithms when applied to an interval database with minimum and maximum temperature of the month for a given year, referring to 37 cities distributed across continents

Lógica BDI fuzzy

Intendding to understand how the human mind operates, some philosophers and psycologists began to study about rationality. Theories were built from those studies and nowadays that interest have been extended to many other areas such as computing engineering and computing science, but with a minimal distinction at its goal: to understand the mind operational proccess and apply it on agents modelling to become possible the implementation (of softwares or hardwares) with the agent-oriented paradigm where agents are able to deliberate their own plans of actions. In computing science, the sub-area of multiagents systems has progressed using several works concerning artificial intelligence, computational logic, distributed systems, games theory and even philosophy and psycology. This present work hopes to show how it can be get a logical formalisation extention of a rational agents architecture model called BDI (based in a philosophic Bratman s Theory) in which agents are capable to deliberate actions from its beliefs, desires and intentions. The formalisation of this model is called BDI logic and it is a modal logic (in general it is a branching time logic) with three access relations: B, D and I. And here, it will show two possible extentions that tranform BDI logic in a modal-fuzzy logic where the formulae and the access relations can be evaluated by values from the interval [0,1]

Uma abordagem fuzzy para a avaliação técnico-econômica de redes de acesso

O surgimento de novas tecnologias e serviços vem impondo mudanças substanciais ao tradicional sistema de telecomunicações. Múltiplas possibilidades de evolução do sistema fazem da etapa de planejamento um procedimento não só desejável como necessário, principalmente num ambiente de competitividade. A utilização de metodologias abrangentes e flexíveis que possam auxiliar no processo de decisão, fundadas em modelos de otimização, parece um caminho inevitável. Este artigo propõe um modelo de programação linear inteiro misto para ajudar no planejamento estratégico de sistemas de telecomunicações, e em particular da rede de acesso. Os principais componentes de custo e receita são identificados e o modelo é desenvolvido para determinar a configuração da rede (serviços, tecnologias, etc) que maximize a receita esperada pelo operador do sistema. O conceito de números fuzzy é adotado para avaliar o risco técnico-econômico em situações de imprecisão nos dados de demanda. Resultados de experimentos computacionais são apresentados e discutidos.

Novos resultados sobre a estabilidade e controle de sistemas nao-lineares utilizando modelos fuzzy e LMI

Relaxed conditions for the stability study of nonlinear, continuous and discrete-time systems given by fuzzy models are presented. A theoretical analysis shows that the proposed method provides better or at least the same results of the methods presented in the literature. Digital simulations exemplify this fact. These results are also used for the fuzzy regulators design. The nonlinear systems are represented by the fuzzy models proposed by Takagi and Sugeno. The stability analysis and the design of controllers are described by LMIs (Linear Matrix Inequalities), that can be solved efficiently by convex programming techniques. The specification of the decay rate, constraints on control input and output are also described by LMIs. Finally, the proposed design method is applied in the control of an inverted pendulum.

Estabilização de sistemas fuzzy T-S incertos usando realimenta̧ão derivativa

In some practical problems, for instance, in the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. Thus, a method for state-derivative feedback design applied to uncertain nonlinear systems is proposed in this work. The nonlinear systems are represented by Takagi-Sugeno fuzzy models during the modeling of the problem, allowing to use Linear Matrix Inequalities (LMIs) in the controller design. This type of modeling ease the control design, because, LMIs are easily solved using convex programming technicals. The control design aimed at system stabilisation, with or without bounds on decay rate. The efficiency of design procedure is illustrated through a numerical example.

Projeto de reguladores fuzzy Takagi-Sugeno utilizando as condições iniciais da planta

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicação de um sistema de Inferência Fuzzy de suporte à decisão para estimação de valores de ações cotadas na Bolsa de Valores de São Paulo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sistematização de projetos de controladores fuzzy através de programação orientada a objetos

Através do uso da programação em linguagem orientada a objetos e, aplicando-se uma técnica de programação específica, é possível gerar um conjunto de classes genéricas cujos objetos representam cada bloco de um controlador fuzzy e também suas variáveis linguísticas. Tais classes, sendo aplicadas de forma sistemática, facilitam a programação de uma variedade de controladores desta natureza. Este trabalho apresenta a referida técnica e mostra os resultados obtidos através de um modelo simulado de um pêndulo rotacional invertido que é controlado por um sistema de controle composto por três controladores fuzzy, projetados e construídos sob este ponto de vista.

Projeto de um controlador Fuzzy Takagi-Sugeno para uma estação de tratamento de esgoto por lodos ativados

Este trabalho propõe o projeto de um controlador Fuzzy do tipo Takagi-Sugeno em uma estação de tratamento de esgoto por lodos ativados. Este tipo de tratamento ocorre na presença de oxigênio, pois microorganismos aeróbios presentes no licor misto irão proporcionar a remoção tanto da matéria carbonácea quanto nutrientes formados por compostos à base de nitrogênio. O controlador atua via mecanismo de aeração e foi projetado para interpolar os ganhos proporcionais e integrativos de três controladores fixos locais que, por sua vez, foram projetados a partir da linearização de um modelo contínuo de balanço de massa de oxigênio. O controlador auxiliará manter a concentração de oxigênio dissolvido desejável na faixa de operação do processo para que ocorra a nitrificação, reação química de oxiredução que transforma amônio em nitrito, que é fundamental para o sucesso do processo, e poderá também economizar energia elétrica utilizada pelo mecanismo de aeração. Os ensaios foram realizados via simulação computacional em quatro cenários idealizados comparando o desempenho do controlador fuzzy e o desempenho de um controlador fixo projetado em um ponto de operação diferente do qual se utilizou como valor de referência na planta. Ao aplicar um degrau no valor de referência estabelecido no cenário de análise, observou-se o tempo de subida, o tempo de acomodação e o erro em regime. Após os ensaios, observou-se que o desempenho do controlador fuzzy nos quesitos tempo de subida e tempo de acomodação em relação ao controlador fixo foi melhor, enquanto nos quesitos sobressinal e erro em regime foi semelhante. Após as análises, concluiu-se que a estratégia de controle escolhida neste trabalho é viável, pois de acordo com o valor auferido de oxigênio dissolvido na entrada da planta, o controlador fuzzy irá interpolar os ganhos proporcionais e integrativos de um controlador fixo projetado na vizinhança deste valor e assim, atuar de forma bastante satisfatória.