The use of Fuzzy Logic Controller (FLC) as a speed controller for Induction Motor (IM) drives is garnering strong researchers' interest since it has proven to achieve superior performance compared to conventional controllers. The aim of this study is to review and investigate the design, operations, and effects of rules reduction for FLC in IM drives. Based on the literature, the most commonly used technique to design FLC Membership Functions (MFs) rule-base and control model is based on engineering skills and experienced behavioral aspects of the controlled system. Simplified fuzzy rules approaches have been introduced to reduce the number of fuzzy rules in order to realize hardware implementation. This study discusses different simplified rules methods applied to IM drives. Most of the proposed methods shared a common drawback in that they lacked systematic procedures for designing FLC rule base. Therefore, this research proposed a methodological approach to designing and simplifying the FLC rule-base for IM drives based on dynamic step response and phase plane trajectory of the second order representation of IM drives systems. The proposed method presents guidance for designing FLC rule-base based on the general dynamic step response of the controlled system. Following the proposed method procedures, a (9, 25, 49) rules size has been designed and simplified to a (5, 7, 9) rules size. The effectiveness and accuracy of the designed rules as well as the simplified rules were verified by conducting simulation analysis of IM drives using MATLAB/Simulink environment. Step speed command performance comparisons were achieved with both standard designed and simplified rules at various speed demands. The simulation results showed that the simplified rules maintain the drive performance and produced similar behavior as the standard designed rules.
The three main parameters used by patients in diabetes management are initial blood glucose, carbohydrate amount, and mealtime difference. In this study, a novel open-loop control algorithm was proposed, which aims to determine the correct value of mealtime difference duration. Unlike current blood glucose estimation methods, this algorithm was focused on determining extreme points that only concern patients such as hyperglycemia and hypoglycemia, instead of predicting all blood glucose trace in the postprandial period. This new approach has made it possible to determine extreme blood glucose values with simple linear equations without using complex models. This algorithm has only three parameters and has been validated in the UVA Padova type 1 diabetes mellitus simulator, which has thirty in-silico patients. The regressions between real and predicted values for hypoglycemia, hyperglycemia, and mean blood glucose were 0.95, 0.99, and 0.98, respectively. Using the proposed algorithm, the severity of hyperglycemia, mean blood glucose, and standard deviation values were reduced, and hypoglycemia events were prevented. Postprandial blood glucose curves have occurred as desired and within normal limits. Furthermore, it was concluded that intersection points of blood glucose curves contain information about the metabolic parameters of the patients, in this study.
Nesne sayma, gıda, medikal, endüstri ve günlük yaşamda farklı görevler için kullanılan bir süreçtir. Bu çalışmada, nesne sayma işleminin gerçekleştirilebilmesi için görüntü işleme tabanlı sistemler incelenmiş ve uygulamalar yapılmıştır. Uygulamalar için nesnelerin bir silo üzerinden akarak serici üzerinden eğimli bir şekilde ilerleyebileceği bir deney düzeneği tasarlanmıştır. Nesnelerin akışını gözlemleyebilecek endüstriyel bir kamera ve lens sistemi kullanılmıştır. Nesnelerin akışını izleyebilmek için sadece arka aydınlatma kullanılmıştır. Nesnelerin akış hızı ve nesnelerin serici çıkışı akabileceği eğim açısı değiştirilebilmektedir. Endüstriyel kamerada fps, piksel frekansı, pozlama süresi, görüntünün çözünürlüğü, ilgilenen alan seçimi, renkli ve renksiz görüntü alımı, görüntüdeki piksellerin kaç bit ile örnekleneceği kullanıcı tarafından seçilebilmektedir. Algoritma tasarımı için Python yazılımı ve OpenCV kütüphanesi kullanılmıştır. Nesne sayımı için 100 adet nohut tanesi belirlenmiş ve belirli bir süre kameradan video kaydı elde edilmiştir. Video üzerinde arka plan çıkarma işlemi uygulanarak sadece nesnelerin beyaz renk olarak görülebileceği ikinci bir video elde edilmiştir. Binary formata dönüştürülen videoda nesne çevresi sınırlayıcı en küçük dikdörtgen koordinat değerleri ve nesne ağırlık merkezi koordinat değerleri elde edilmiştir. Video görüntüsü üzerinde sabit tek ve çift sanal çizgiler çekilerek sayma işleminin gerçekleştirileceği metotlar geliştirilmiştir. Koordinat değerlerinin ve sanal çizgilerin sayma işlemi için kullanılmasında ortaya çıkan avantaj ve dezavantajlar bu çalışma sonucunda tartışılmıştır.
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