771 resultados para Type-2 fuzzy logic control system


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In this work was developed a fuzzy computational model type-2 predictive interval, using the software of the type-2 fuzzy MATLAB toolbox, the final idea is to estimate the number of hospitalizations of patients with respiratory diseases. The interest in the creation of this model is to assist in decision makeshift hospital environment, where there are no medical or professional equipment available to provide the care that the population need. It began working with the study of fuzzy logic, the fuzzy inference system and fuzzy toolbox. Through a real database provided by the Departamento de Informática do Sistema Único de Saúde (DATASUS) and Companhia de Tecnologia de Saneamento Básico (CETESB), was possible to start the model. The analyzed database is composed of the number of patients admitted with respiratory diseases a day for the public hospital in São José dos Campos, during the year 2009 and by factors such as PM10, SO2, wind and humidity. These factors were analyzed as input variables and, through these, is possible to get the number of admissions a day, which is the output variable of the model. For data analysis we used the fuzzy control method type-2 Mamdani. In the following steps the performance developed in this work was compared with the performance of the same model using fuzzy logic type-1. Finally, the validity of the models was estimated by the ROC curve

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The study assessed the economic efficiency of different strategies for the control of post-weaning multi-systemic wasting syndrome (PMWS) and porcine circovirus type 2 subclinical infection (PCV2SI), which have a major economic impact on the pig farming industry worldwide. The control strategies investigated consisted on the combination of up to 5 different control measures. The control measures considered were: (1) PCV2 vaccination of piglets (vac); (2) ensuring age adjusted diet for growers (diets); (3) reduction of stocking density (stock); (4) improvement of biosecurity measures (bios); and (5) total depopulation and repopulation of the farm for the elimination of other major pathogens (DPRP). A model was developed to simulate 5 years production of a pig farm with a 3-weekly batch system and with 100 sows. A PMWS/PCV2SI disease and economic model, based on PMWS severity scores, was linked to the production model in order to assess disease losses. This PMWS severity scores depends on the combination post-weaning mortality, PMWS morbidity in younger pigs and proportion of PCV2 infected pigs observed on farms. The economic analysis investigated eleven different farm scenarios, depending on the number of risk factors present before the intervention. For each strategy, an investment appraisal assessed the extra costs and benefits of reducing a given PMWS severity score to the average score of a slightly affected farm. The net present value obtained for each strategy was then multiplied by the corresponding probability of success to obtain an expected value. A stochastic simulation was performed to account for uncertainty and variability. For moderately affected farms PCV2 vaccination alone was the most cost-efficient strategy, but for highly affected farms it was either PCV2 vaccination alone or in combination with biosecurity measures, with the marginal profitability between 'vac' and 'vac+bios' being small. Other strategies such as 'diets', 'vac+diets' and 'bios+diets' were frequently identified as the second or third best strategy. The mean expected values of the best strategy for a moderately and a highly affected farm were £14,739 and £57,648 after 5 years, respectively. This is the first study to compare economic efficiency of control strategies for PMWS and PCV2SI. The results demonstrate the economic value of PCV2 vaccination, and highlight that on highly affected farms biosecurity measures are required to achieve optimal profitability. The model developed has potential as a farm-level decision support tool for the control of this economically important syndrome.

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Os doentes com diabetes mellitus tipo 2 apresentam predisposição para a retenção de sódio e são frequentemente hipertensos. No entanto, os mecanismos implicados na dificuldade do rim diabético em mobilizar o sódio são, ainda, pouco compreendidos. Os peptídeos da família das guanilinas estão envolvidos na regulação do transporte de electrólitos e água nos epitélios intestinal e renal, através da activação do receptor guanilato ciclase-C (GC-C) e subsequente libertação intracelular de GMPc. O objectivo do presente estudo foi a avaliação da actividade do sistema dos peptídeos das guanilinas (SPG) e do seu papel na regulação do balanço de sódio num modelo animal de diabetes tipo 2. Ratinhos machos C57BL/6 foram submetidos a uma dieta com alto teor de gordura e rica em hidratos de carbono simples (ratinhos diabéticos) ou a uma dieta normal (ratinhos controlo). A expressão renal e intestinal da guanilina (GN), uroguanilina (UGN) e do receptor GC-C assim como os níveis de GMPc na urina e plasma foram avaliados nos ratinhos controlo e diabéticos, durante a ingestão de dietas normo (NS) e hiper-salina (HS). Nos ratinhos diabéticos, durante a dieta NS verificou-se um aumento significativo da pressão arterial que foi acompanhado de redução da expressão do ARNm da GN, UGN e do GC-C no intestino e de aumento da expressão de ARNm da UGN no rim. A dieta HS induziu um aumento da expressão do ARNm da UGN no jejuno dos ratinhos controlo mas não nos diabéticos. Os ratinhos diabéticos apresentaram níveis urinários de GMPc inferiores aos controlos, em condições de dieta NS. Em conclusão, os nossos resultados sugerem que na diabetes tipo 2 ocorre uma redução da actividade intestinal do SPG que é acompanhada por um aumento compensatório da actividade renal do SPG. A diminuição da actividade do SPG intestinal na diabetes tipo 2 deve-se não só a uma redução da expressão dos peptídeos GN e UGN, mas também a uma redução da expressão do seu receptor, GC-C. Estes resultados sugerem que o SPG pode contribuir para a sensibilidade ao sódio na diabetes.

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Fuzzy logic controllers (FLC) are intelligent systems, based on heuristic knowledge, that have been largely applied in numerous areas of everyday life. They can be used to describe a linear or nonlinear system and are suitable when a real system is not known or too difficult to find their model. FLC provide a formal methodology for representing, manipulating and implementing a human heuristic knowledge on how to control a system. These controllers can be seen as artificial decision makers that operate in a closed-loop system, in real time. The main aim of this work was to develop a single optimal fuzzy controller, easily adaptable to a wide range of systems – simple to complex, linear to nonlinear – and able to control all these systems. Due to their efficiency in searching and finding optimal solution for high complexity problems, GAs were used to perform the FLC tuning by finding the best parameters to obtain the best responses. The work was performed using the MATLAB/SIMULINK software. This is a very useful tool that provides an easy way to test and analyse the FLC, the PID and the GAs in the same environment. Therefore, it was proposed a Fuzzy PID controller (FL-PID) type namely, the Fuzzy PD+I. For that, the controller was compared with the classical PID controller tuned with, the heuristic Ziegler-Nichols tuning method, the optimal Zhuang-Atherton tuning method and the GA method itself. The IAE, ISE, ITAE and ITSE criteria, used as the GA fitness functions, were applied to compare the controllers performance used in this work. Overall, and for most systems, the FL-PID results tuned with GAs were very satisfactory. Moreover, in some cases the results were substantially better than for the other PID controllers. The best system responses were obtained with the IAE and ITAE criteria used to tune the FL-PID and PID controllers.

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This work deals with an hybrid PID+fuzzy logic controller applied to control the machine tool biaxial table motions. The non-linear model includes backlash and the axis elasticity. Two PID controllers do the primary table control. A third PID+fuzzy controller has a cross coupled structure whose function is to minimise the trajectory contour errors. Once with the three PID controllers tuned, the system is simulated with and without the third controller. The responses results are plotted and compared to analyse the effectiveness of this hybrid controller over the system. They show that the proposed methodology reduces the contour error in a proportion of 70:1.

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This paper presents a novel intelligent multiple-controller framework incorporating a fuzzy-logic-based switching and tuning supervisor along with a generalised learning model (GLM) for an autonomous cruise control application. The proposed methodology combines the benefits of a conventional proportional-integral-derivative (PID) controller, and a PID structure-based (simultaneous) zero and pole placement controller. The switching decision between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using a fuzzy-logic-based supervisor, operating at the highest level of the system. The supervisor is also employed to adaptively tune the parameters of the multiple controllers in order to achieve the desired closed-loop system performance. The intelligent multiple-controller framework is applied to the autonomous cruise control problem in order to maintain a desired vehicle speed by controlling the throttle plate angle in an electronic throttle control (ETC) system. Sample simulation results using a validated nonlinear vehicle model are used to demonstrate the effectiveness of the multiple-controller with respect to adaptively tracking the desired vehicle speed changes and achieving the desired speed of response, whilst penalising excessive control action. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

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The aim of this work is to evaluate the fuzzy system for different types of patients for levodopa infusion in Parkinson Disease based on simulation experiments using the pharmacokinetic-pharmacodynamic model. Fuzzy system is to control patient’s condition by adjusting the value of flow rate, and it must be effective on three types of patients, there are three different types of patients, including sensitive, typical and tolerant patient; the sensitive patients are very sensitive to drug dosage, but the tolerant patients are resistant to drug dose, so it is important for controller to deal with dose increment and decrement to adapt different types of patients, such as sensitive and tolerant patients. Using the fuzzy system, three different types of patients can get useful control for simulating medication treatment, and controller will get good effect for patients, when the initial flow rate of infusion is in the small range of the approximate optimal value for the current patient’ type.

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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.

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Study design: Association study Objective: To analyze the association between different biological/behavioral risk factors and blood pressure in a sample of type 2 diabetes mellitus patients with poor glycemic control. Methods: A sample of 121 type 2 diabetic patients was selected in the Public Healthcare System in a middle size Brazilian city. Blood pressure was measured using an aneroid device, previously calibrated. Six determinants of blood pressure were taken into count: age, hypoglycemic agents, general obesity, abdominal obesity, eating behaviors and physical activity level. Results: The type 2 diabetic patients presented mean age of 60.1±8.9 years-old and, at least, one risk factor. Eating behaviors (OR adj= 0.31 [0.12-0.75]) and sports practice (OR adj= 0.12 [0.02-0.75]) constituted protective factors associated with lower systolic blood pressure. On the other hand, age was positively associated with high systolic blood pressure (OR adj= 3.81 [1.39-10.38]). Patients with 5-6 risk factors, presented higher values of systolic and (F= 3.857; p= 0.011 [post hoc with p= 0.039]), diastolic blood pressure (F= 4.158; p= 0.008 [post hoc with p= 0.036]) and increased occurrence of hypertension (p= 0.010). Conclusion: Our findings indicate that, behavioral variables were important determinants of blood pressure in type 2 diabetic patients with poor glycemic control and clustering of behavioral and biological risk factors increase the hypertension occurrence.

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The main objective of the presented study is the development of a predictive interval type-2 fuzzy inference system in order to estimate the mortality risk for a newborn, to be used as an auxiliary tool for decision making in medical centers where there is a lack of professionals for this purpose and, afterwards, to compare its performance to a type-1 fuzzy system. The input variables were chosen due to their acquisition ‘simplicity, not involving any invasive tests, such as blood tests or other specific tests. The variables are easily obtained in the first few minutes of life: birth weight, gestational age at delivery, 5-minute Apgar score and previous report of stillbirth. Databases from the DATASUS were used to validate the model. 1351 records from the city of São José dos Campos, a mid-sized city in the São Paulo state’s countryside, were considered in this study. Finally, an analysis using the ROC curve was performed to estimate the model’s accuracy

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Cost-effectiveness and budget impact of saxagliptine as additional therapy to metformin for the treatment of diabetes mellitus type 2 in the Brazilian private health system Objectives: To compare costs and clinical benefits of three additional therapies to metformin (MF) for patients with diabetes mellitus type 2 (DM2). Methods: A discrete event simulation model seas built to estimate the cost-utility ratio (cost per quality-adjusted life years [QALY)) of saxagliptine as an additional therapy to MF when compared to rosiglitazone or pioglitazone. A budget impact model (BIM) was built to simulate the economic impact of saxagliptine use in the context of the Brazilian private health system. Results: The acquiring medication costs for the hypothetical patient group analyzed in a time frame of three years, were R$ 10,850,185, R$ 14,836,265 and R$ 14,679,099 for saxagliptine, pioglitazone and rosiglitazone, respectively. Saxagliptine showed lower costs and greater effectiveness in both comparisons, with projected savings for the first three years of R$ 3,874 and R$ 3,996, respectively. The BIM estimated cumulative savings of R$ 417,958 with the repayment of saxagliptine in three years from the perspective of a health plan with 1,000,000 covered individuals. Conclusion: From the perspective of private paying source, the projection is that adding saxagliptine with MF save costs when compared with the addition of rosiglitazone or pioglitazone in patients with DM2 that have not reached the HbA1c goal with metformin monotherapy. The BIM of including saxagliptine in the reimbursement lists of health plans indicated significant savings on the three-year horizon.

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Solar drying is one of the important processes used for extending the shelf life of agricultural products. Regarding consumer requirements, solar drying should be more suitable in terms of curtailing total drying time and preserving product quality. Therefore, the objective of this study was to develop a fuzzy logic-based control system, which performs a ?human-operator-like? control approach through using the previously developed low-cost model-based sensors. Fuzzy logic toolbox of MatLab and Borland C++ Builder tool were utilized to develop a required control system. An experimental solar dryer, constructed by CONA SOLAR (Austria) was used during the development of the control system. Sensirion sensors were used to characterize the drying air at different positions in the dryer, and also the smart sensor SMART-1 was applied to be able to include the rate of wood water extraction into the control system (the difference of absolute humidity of the air between the outlet and the inlet of solar dryer is considered by SMART-1 to be the extracted water). A comprehensive test over a 3 week period for different fuzzy control models has been performed, and data, obtained from these experiments, were analyzed. Findings from this study would suggest that the developed fuzzy logic-based control system is able to tackle difficulties, related to the control of solar dryer process.

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At the present time there is a high pressure toward the improvement of all the production processes. Those improvements can be sensed in several directions in particular those that involve energy efficiency. The definition of tight energy efficiency improvement policies is transversal to several operational areas ranging from industry to public services. As can be expected, agricultural processes are not immune to this tendency. This statement takes more severe contours when dealing with indoor productions where it is required to artificially control the climate inside the building or a partial growing zone. Regarding the latter, this paper presents an innovative system that improves energy efficiency of a trees growing platform. This new system requires the control of both a water pump and a gas heating system based on information provided by an array of sensors. In order to do this, a multi-input, multi-output regulator was implemented by means of a Fuzzy logic control strategy. Presented results show that it is possible to simultaneously keep track of the desired growing temperature set-point while maintaining actuators stress within an acceptable range.

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In order to address the increasing compromise of user privacy on mobile devices, a Fuzzy Logic based implicit authentication scheme is proposed in this paper. The proposed scheme computes an aggregate score based on selected features and a threshold in real-time based on current and historic data depicting user routine. The tuned fuzzy system is then applied to the aggregated score and the threshold to determine the trust level of the current user. The proposed fuzzy-integrated implicit authentication scheme is designed to: operate adaptively and completely in the background, require minimal training period, enable high system accuracy while provide timely detection of abnormal activity. In this paper, we explore Fuzzy Logic based authentication in depth. Gaussian and triangle-based membership functions are investigated and compared using real data over several weeks from different Android phone users. The presented results show that our proposed Fuzzy Logic approach is a highly effective, and viable scheme for lightweight real-time implicit authentication on mobile devices.