LEE- Kontrol ve Otomasyon Mühendisliği-Yüksek Lisans
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ÖgeImproved fuzzy logic based edge detection method on clinical images(Graduate School, 2022-01-07)Signal processing is the main field combining electrical engineering and mathematics, used to analyze digital and analog signals. Signal processing deals with the storage, compression, filtering and other processing of signals. These signals can be sound signals, image signals, and other signals. Nowadays images are essential thing for many area. Images can be used in space researches, military applications, marine workings, automotive industry, environment, agriculture and medical science. The area where the signal type is processed is that the input is an image, and the output is also an image, which is called image processing. Image Processing is one of the main research area in the disciplines of computer science and engineering. Image processing is a methods which performs operations on an image, on account of get an information from image. The progress of image processing are improved by the help of: the development of technology, the development of discrete theory, the demand for a pretty wide range of applications. It can be divided into digital and analog image processing. Image processing for analog images is used for hard copies of photos. Digital image processing uses computers to process digital images. Image processing has various kind of application such as sharpening, blurring, contrast adjustment, and edge detection etc. Edge detection is helpful for applications in the fields such as fingerprint matching, medical diagnosis, license plate detection, biomedical imaging, pattern recognition and machine vision. Edge detection technique makes the high intensity valued pixels visible. Edge detection is a compelling assignment. When edge detection must be applied to noisy images, it becomes more difficult. The idea of fuzzy logic helps to get rid of this problem with expert knowledge. The concept of fuzzy logic was first proposed in the 1960s by Professor Lütfi Aliasker Zade in Berkeley. Lütfi Aliasker Zade is committed to translating natural language into computer language, but it is not easy to translate into computer language terms 0 and 1. Zade proposed a shape of polyvalent logic within which the truth valuation of variables is also any real number between 0 and 1 whereas classical logic theory is utilizing with values false or true. Fuzzy logic can be summarized as predicated on the observation that individuals make decisions supported vague and non-numerical information. Fuzzy models are numerical implies of speaking to dubiousness and uncertain data. These models have the inclination of deciphering and controlling information and information that are non-certain. Additionally, it's conceivable to characterize linguistic variables like brief, exceptionally brief, long, or exceptionally long with fuzzy logic. Lütfi Zade's proposed theory fuzzy logic has been applied to various fields such as robotics, artificial intelligence, modeling and controlling system which is nonlinear or digital image processing. These fields used type-1 fuzzy logic until Prof. Lütfi A. Zade presented type-2 fuzzy logic in 1975. Fuzzy logic's type-2 theory was improved for uncertainties and non-linearity due on type-1 fuzzy rules, it shows fuzzy logic frameworks on type-2 are more fruitful than fuzzy logic frameworks on type-1 to unravel vulnerabilities. Be that as it may, working with fuzzy logic frameworks on type-2 are distant more advanced than working with fuzzy logic frameworks on type-1. In this thesis we will talk about a type-1 edge detection with fuzzy logic implementation for medical brain images, with the assistance of digital image, and digital image processing. This thesis gives you the performance comparison of widely used edge detection methods and improved edge detection with fuzzy logic method with interpreting digital images with the help of image enhancement and restoration and performing operations on images such as blurring, contrast adjustment. Different sources of digital images will be tested and results for each source will be provided.
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ÖgeFuzzy logic based clutch torque curve detection algorithm for heavy duty vehicles(Graduate School, 2023-01-24)In this thesis, a fuzzy logic-based clutch torque curve learning algorithm is proposed as the second method to eliminate the mentioned disadvantages. The torque curve can be determined with this method without the necessity for any specific maneuver and activation conditions. Using a reference point on the curve, the fuzzy logic-based algorithm determines the position value corresponding to the reference point with respect to different clutch temperatures and the first torque transfer points. In this study, 581 Nm was chosen as the reference point. The fuzzy logic theory was introduced by L. A. Zadeh in 1965. Since then, it has been utilized in numerous fields, including the automotive, transportation, robotics, and chemical industries. The theory basically transforms the relationship between concepts into linguistic rules and permits expert opinions and experiences to be incorporated into system models. Fuzzy controllers consist of three main parts: fuzzifier, rule-based inference engine, and defuzzifier. Mamdani and Takagi-Sugeno type of fuzzy controllers are the most commonly used. MATLAB-Simulink was used for simulation studies. First of all, the conventional algorithm model was developed. The activation conditions, timer, and curve calculation functions used in the model are mentioned in detail. Secondly, two different fuzzy controllers, Takagi-Sugeno and Mamdani types, were designed. The purpose of designing different types of controllers is to compare the performances of the controllers for this problem. While designing the controllers, MATLAB's "Fuzzy Logic Designer" interface was utilized. In order to make a realistic comparison, the same input membership functions and rules are used in the controllers. The inputs of the controllers are selected as the clutch temperature and the first torque transfer point. Three membership functions are defined for each input: "low", "medium" and "high". The output of the controllers is the clutch position corresponding to the reference torque. As with the inputs, three different output membership functions are defined as "low," "medium," and "high" for both controllers. During the design of fuzzy controllers, the relationship between inputs and outputs was determined by analyzing data collected from multiple vehicles. After designing both controllers, a mechanism was created to choose between the conventional algorithm and the fuzzy-based algorithm. The decision mechanism basically compares the reference clutch position values obtained from the two strategies. If the difference between the calculated reference values exceeds a predetermined upper threshold, the error is detected, and the curve obtained from the fuzzy-based strategy becomes equal to the final output. If the difference between the calculated reference values is below a lower threshold, the error is deactivated, and the curve obtained from the conventional algorithm becomes equal to the final output. Thus, as the traditional algorithm will not be activated until the first launch maneuver, the error value will be high and the fuzzy-based strategy will be effective. So, the mechanism eliminates the feeling of poor performance on the first launch. Moreover, the output of the fuzzy controller will be continuously updated based on the change in clutch temperature and the first torque transfer point while driving. The fuzzy controller will be activated if an error is detected, preventing incorrect torque curve learning situations. For testing and validating the developed model, a two-step test procedure was created. First, launch maneuver data was collected for three different clutch temperature ranges: low (40-70°C), medium (70-90°C), and high (90-120°C) from a test vehicle with a 28-ton, construction truck variant. The relationship between traditional and fuzzy controller-based algorithms was examined by feeding the vehicle data to the generated MATLAB-Simulink model. This study was carried out separately for models using Takagi-Sugeno and Mamdani type fuzzy controllers. The obtained clutch torque curves were compared for 40, 70, and 100 °C clutch temperatures, one value from each temperature zone. In the second step of the test, the torque curves obtained from the conventional algorithm, Mamdani, and Takagi-Sugeno type fuzzy controllers for different clutch temperatures were validated by performing launch maneuvers on the same test vehicle. For each test, the maneuvers were repeated with the same gear, accelerator pedal, and road conditions. The verification was done by examining the difference between engine and clutch torque during the launch maneuver. A large difference between torque values indicates that the clutch is in the wrong position. For this reason, the difference between the torque values was defined as the error. Three different performance indexes ISE, ITSE and ITAE were used to compare the performance of the strategies analytically. Since the ITSE and ITAE indices are time-dependent, they evaluate launch maneuvers in terms of duration. The test results were analyzed in three sections as low, medium, and high. At low clutch temperatures, both Mamdani and Takagi-Sugeno fuzzy controllers outperform the conventional algorithm. Moreover, Mamdani provides better results according to ISE index, whereas Sugeno outperforms according to ITAE and ITSE indices at low clutch temperatures. The main reason for this is that when a Sugeno-type fuzzy controller is used, the launch times are reduced. For medium clutch temperatures, all three strategies were yielded similar results. As at low temperatures, Mamdani provides better results according to ISE index, whereas Sugeno outperforms according to ITAE index at medium clutch temperatures. According to the ITSE index, the performance of the two strategies is equal. For all three indices, the traditional algorithm has the lowest performance. However, there is no dramatic difference in the results of the three strategies. For high clutch temperatures, Sugeno has the worst performance according to all three indices. The main reason for this is that the Sugeno type fuzzy controller is much more sensitive to high clutch temperatures than the Mamdani type fuzzy controller. In addition, Mamdani type fuzzy controller has the best performance for all three indices. In general, it was observed that fuzzy controllers improved clutch torque curves. On the other hand, fuzzy controllers increased computational load and simulation times. Both types of fuzzy controllers have improved the performance of the first launch maneuvers. Sugeno type fuzzy controller is highly sensitive to changes in high clutch temperatures. Therefore, it showed poor performance at high temperatures. The Mamdani-type fuzzy controller, on the other hand, succeeded in all three test scenarios.
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ÖgeAsenkron motorun farklı kontrol yöntemleri ile hız kontrolü ve raylı sistemlere uygulanması(Lisansüstü Eğitim Enstitüsü, 2023-02-09)Hareketin olduğu tüm alanlarda motorlara da ihtiyaç vardır. Başta üretim, ulaşım, enerji gibi genel sektörler olmak üzere gündelik hayatımızda karşımıza çıkan küçük ev aletleri, beyaz eşyalar ve akla gelen çoğu alanda motorlar kullanılmaktadır. Artan dünya nüfusu ve modernizasyon ile birlikte motorlara olan ihtiyaç gün geçtikçe artmaktadır. Motor, kaba bir tabirle kullandığı enerjiyi hareket enerjisine çeviren makinelerdir. Kullanılan enerji katı yakıt, sıvı yakıt ve elektrik gibi çeşitli türlerde olabilir, bu yakıtları kullanan motorların farklı kullanım alanları vardır. Bu motorların birbirlerine göre avantajları ve dezavantajları bulunmaktadır. Çevre kirliliği günümüzde oldukça artmıştır ve gün geçtikçe de artmaya devam etmektedir, bu sebeple her alanda karşımıza çıkan ve çok yaygın şekilde kullanılan motorların çevre kirliliği açısından zararsız olması oldukça önemlidir. Elektrik motorları, yüksek verimleri, geniş tork ve hız karakteristikleri ve çevre dostu olmaları sebebiyle geniş bir kullanım alanı bulmaktadırlar. Farklı sınıflandırmalara göre çeşitli tipte elektrik motorları bulunmaktadır ve bu elektrik motorlarının farklı kullanım alanları, avantajları ve dezavantajları bulunmaktadır. Tez kapsamında simülasyonu yapılacak olan asenkron motorlar çok basit yapılıdırlar, bu sebeple oldukça ucuz, küçük boyutlu ve dayanıklı bir elektrik motoru türüdür. Benzer şekilde yapılarında fırça ve komütatör olmadığı için kıvılcım gibi güvenlik sorunları da oluşturmazlar ve bakım gereksinimleri yoktur veya çok kısıtlıdır. Asenkron motorlar, ulaşım ve üretim sektörü başta olmak üzere endüstride çok yaygındır. Asenkron motorlar, çalışma mantıkları gereği tek bir alternatif akım ile beslenirler. Statorun beslendiği bu akım yardımıyla rotorda akım endüklenir ve hareket oluşur, bu sebepten dolayı indüksiyon motoru ismiyle de isimlendirilirler. Basit çalışma mantığının getirdiği avantajlarının yanı sıra bazı dezavantajları da bulunmaktadır. Bunların başında DC motorlar gibi ayrı akımlar kullanılarak tork ve akı kontrolünün yapılamadığı gelmektedir, bu sebeple asenkron motorların kontrol yapıları ayrı akım ile sürülen elektrik motorlarına göre zordur. Ayrıca asenkron motorların doğrusal olmayan yapıları kontrol edilmelerini zorlaştırmaktadır. Asenkron motorların farklı kontrol yöntemleri mevcuttur, bunların başında skaler ve vektörel kontrol gelmektedir. Belirtilen iki yöntemin kullanım amaçları ve avantajları farklıdır. Bu çalışma kapsamında daha hassas kontrol sonuçları verebilen vektörel kontrol çalışılmıştır. Vektörel kontrol de kendi içerisinde doğrudan ve dolaylı vektörel kontrol olmak üzere ikiye ayrılmaktadır, çalışma kapsamında akı değerine ve pozisyonuna doğrudan ihtiyaç duyulmayan dolaylı vektörel kontrol yöntemi tercih edilmiştir. Vektörel kontrol ile birlikte asenkron motor bir DC motor gibi iki ayrı akım ile birlikte kontrol edilir ve bu sebeple yapılan kontrol işlemi nispeten basit bir hale getirilmiş olur. Ulaşım sektöründeki araç sayısı gün geçtikçe artmaktadır, bu sebeple ulaşım sektöründe kullanılan motorların çevreci ve yüksek verimli olması oldukça önemlidir. Demiryolu ulaşım araçları düşünüldüğünde yüksek çalışma saatleri, uzun süreli kullanım ömürleri ön plandadır, dolayısıyla itki sisteminin en önemli parçası olan motorun verimi çok önemlidir. Mıknatıslı elektrik motorları, verimin yüksek olduğu tüm alanlarda iyi bir alternatif olmaktadır, fakat yaşanan mıknatıs temini problemleri sebebiyle mıknatıslı elektrik motorlarındaki yaygın kullanım gün geçtikçe azalmaktadır. Metrolar, büyük şehirler için iyi bir ulaşım aracı alternatifidir, çünkü demiryollarını kullandıkları ve yer altından gittikleri için ek bir kara yolu şeridi işgal etmezler. Benzer sebeple insan yoğunluğunun fazla olduğu büyük şehirlerde, trafiksiz bir çözüm sundukları için kullanımları gün geçtikçe yaygınlaşmaktadır. Çalışma kapsamında MATLAB Simulink ortamında modellenen asenkron motor modeli bir metro aracında kullanılacak şekilde tasarlanmıştır. Metrolar çalışma prensipleri gereği genelde şehir içlerinde çalıştıkları için emniyet sebebiyle belirli bir hızın üstünde çalışmaları istenmez, ayrıca yolcu konforu ve emniyeti sebebiyle de belirli bir ivme üstüne çıkmaları engellenir. Bu limitler modelleme yapılırken dikkate alınmıştır, ayrıca asenkron motorun yapısı gereği oluşturulan modelin maksimum gerilim, maksimum tork ve maksimum güç üstüne çıkması engellenmiştir. Asenkron motor kontrolü düşünüldüğünde yukarıda bahsedilen emniyet ve konfor sebebiyle ivme kontrol altında tutulmalıdır, hız ve konum ise hassas bir şekilde kontrol edilmelidir, çünkü metrolardan belirlenen konumlarda ve çok küçük hata payı içerisinde durmaları beklenir. Ayrıca hız ve konum kontrolü için aşım istenen bir durum değildir. Bu performans kriterleri oluşturulan kontrol yapıları için göz önüne alınmıştır. Asenkron motorlar, diğer elektrik motorları gibi çalışırken ısınırlar, bu sebeple motor parametrelerinde ısınma sonucu değişimler oluşur. Ayrıca yukarıda bahsedildiği gibi asenkron motorların doğrusal olmayan yapılarından dolayı oluşturulan modelde belli kabuller yapılmıştır. Tüm bu model kaynaklı bilinmezlikler ve parametrik değişimlere ek olarak, metronun hareketini sürdürdüğü yoldan kaynaklı bilinmezlikler ve değişimler ve metro içerisine binen yolculardan dolayı oluşan toplam ağırlık değişimi yapılan kontrol yapısının dayanıklı olmasını gerektirir. Bu sebeple tasarlanan kontrol yapısının dayanıklı olması ve sistemi farklı koşullarda da başarılı bir şekilde kontrol edebilmesi de bir performans kriteri olarak göz önüne alınmıştır. Asenkron motor kontrolünde PID, PI-PD, bulanık kontrol, kayan kipli kontrol ve doğrusal olmayan dinamik tersleme yöntemleri kullanılmıştır. Bu kontrol yöntemleri asenkron motorun hız kontrolünü yapabilmek için tasarlanmıştır. Tasarımları yapılan kontrol yapıları istenen performans kriterlerine göre kıyaslanmıştır. Kullanılan kontrol yöntemlerinde tasarım yapılırken Osman Kaan Erol ve İbrahim Eksin tarafından ortaya atılan büyük patlama büyük çöküş optimizasyon yönteminden faydalanılmıştır. Çalışmada son olarak yapılan tasarımların karşılaştırmalı sonuçları yer almaktadır.
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ÖgeTrajectory tracking control of a quadrotor with reinforcement learning(Graduate School, 2023-01-23)Drone control algorithms are usually broken down into several steps. The innermost parts of a drone control algorithm are angle and angular velocity control loops. Whether it is fixed-wing or rotary-wing, these control loops conventionally consist of PID based controllers. Although a PID controller can control these loops successfully, it may not lead the outer loops to desired positions or velocities. An outer loop designed to manage these situations can be done with conventional controller loops. However, these kinds of controllers are heavily model-dependent and often require tuning. Motivated by this situation, the aim of the presented study is to show that reinforcement learning based algorithms can control a quadrotor drone without prior knowledge of the model. The most preferred model-free reinforcement algorithms in the literature are DDPG, TRPO, and PPO. The studies that use state-of-the-art reinforcement learning methods for quadcopter control are compared, and it is concluded that PPO is the best choice to begin with. An actor-critic neural network for PPO-clip, the most successful version of PPO, is built and trained on a custom Gym environment. The environment is a quadrotor model that covers fundamental dynamics. This study is composed of six chapters. In the first chapter, motivation of research and literature review are given. In the second chapter, the theoretical background to construct a quadrotor model is given, and a general picture of reinforcement learning and model-free algorithms is drawn. In the third chapter, a custom simulation environment using the features of Gym library is designed. Then, the neural network based controller is designed, in the fourth chapter. Next, the agent is trained in the custom environment, in the fifth chapter. The simulation results of hovering and trajectory tracking tests are given. In the last chapter, it is concluded that a model-free reinforcement learning-based neural network without any additional control loop can control a quadrotor, and possible future works for this study are discussed.
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ÖgeFunctional safety for heavy-duty transmissions(Graduate School, 2022-09-22)The number of electrical and electronic equipment and software used in vehicles is increasing day by day. Apart from passive safety precautions for these hardware and software used, now active precautions are also taken. While the seat belt was a passive safety measure in the first years when vehicles became a necessity for the society, many software and hardware measures are now taken for the safety of the driver and passengers. Thanks to the autonomous transportation, the driver's place in transportation is decreasing, while his safety and security are gaining more and more importance. A system or piece of hardware must operate appropriately in accordance with the system's inputs in order for functional safety to be a component of the overall safety framework. To put it another way, functional safety refers to the capacity to recognize potentially dangerous circumstances and to trigger a protective or corrective device or mechanism to stop the development of hazardous events or to lessen their potential effects. The only means for the driver to act in an emergency while driving an automobile is to press the brake pedal. However, thanks to the software created thanks to functional safety, accidents can be prevented by intervening to the vehicle faster than the driver in an unexpected situation. Electrical, electronic, and programmable electronic everything is determined within the framework of certain rules and steps, functional safety analyzes and safety levels within the purpose of the IEC 61508 standard. Functional safety is included in the ISO 26262 standard group, being customized for the automotive sector. The ISO 26262 standard series describe how software and hardware for an automotive should be developed in certain road conditions and accident situations. In this thesis, the subject of functional safety will be examined in the automatic transmission system used in heavy vehicles. Today, due to globalization and the increase in consumer needs, logistics and transportation sectors gain more importance. Transportation is of great importance in these sectors and heavy vehicles have a large share in this sector. Trucks, trucks, etc., for both the safety of people and the transportation of products without any damage. It is important that vehicles are safe and secure. Among the working subjects of the automotive industry, the transmission software and designs of heavy-duty vehicles have an important value. The heavy-duty transmission to be analyzed is an automated manual transmission, with 16 forward and 4 reverse gears. Gear shifts are not only with synchromesh, but also by using 3-stage actuators, more combinations are created with less gears, and a lighter transmission is designed than expected. However, functional safety becomes more important in heavy-duty vehicles that have more hardware and software in terms of software and hardware. Because, in heavy-duty vehicles, the gearbox not only provides regular and desired torque transmission, but also fulfills different duties depending on the service type. Therefore, safety analyzes and created scenarios are investigated in more detail. In this research, firstly, the safety analysis of the heavy-duty vehicle was carried out according to the ISO 26262 standard group. In order to make a more detailed examination as the system where the safety analysis will be made, the system limits have been determined as automatic transmission and actuators. Then, the problems that may arise in the vehicle and transmission are considered and it is determined what kind of dangers may occur. Considering these hazards, hazard and risk analysis has been made for specific scenarios. What kind of safety goals should be taken against the hazards that may arise because of the hazard and risk analysis and how long it should take are defined in the functional safety concept. The analysis made was examined in detail and the safety requirements were established for the transmission software. The safety targets and requirements that emerged as a result of the safety analyzes were tested in the simulation environment. By means of model-based software, a dynamic model of the heavy-duty vehicle is created, and simple transmission algorithms are demonstrated. By creating virtual hazards and scenarios in Matlab & Simulink environment, vehicle models with and without functional safety software are compared.