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YILDIRIM, ALPER

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YILDIRIM

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ALPER

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2022 - 20235
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Now showing 1 - 5 of 5
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    PublicationOpen Access
    Fuzzy decision based modeling of rheostatic brake system for autonomous land vehicles
    (2022-09-01) YILDIRIM, ALPER; Sünkün S., Parlak B. O. , Yıldırım A., Yavaşoğlu H. A.
    The most fundamental characteristic of autonomous vehicles (AVs) is their autonomy. However, due to the dynamic operating environment of the vehicle, their control algorithms may make imprecise, approximate, and unreliable decisions. Therefore, there is a need for the creation of more robust driving algorithms, notably consistent obstacle avoidance algorithms. Occasionally, the vehicle must come to a complete stop in order to avoid obstacles. In this situation, the engine brake control of the car can be engaged. In this study, a fuzzy model was proposed to effectively brake autonomous land vehicles, with an electrical braking system known as rheostatic braking. Since a rheostatic braking system (RBS) is employed, the input values of the fuzzy controller for this designed modeling are vehicle speed and ground slipperiness, and the output value is the rheostat resistance value. In the developed fuzzy controller, Mamdani inference and Aggregation methods were utilized. In addition to these two methods, the fuzzy controller also provides the output of the centroid, bisector, average of the maximum, smallest of the maximum and largest of the maximum sharpening methods to the user. Finally, using the Python programming language and the Tkinter library, the graphical user interface displays the linguistic expression and membership degree of the user\"s inputs, the final fuzzy output graph, and the exact outputs from all clarification methods (GUI).
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    PublicationOpen Access
    Parameter estimation of magnetic growing rod with output error method
    (2023-10-11) YILDIRIM, ALPER; Yildirim A., Akgün G., Çokatar S., Demir U.
    This study focuses on a magnetic controlled growing rods (MCGR) used in the treatment of early-onset scoliosis. In this study, the Lyapunov direct method-based output error method, which is iterative adaptive by online, is used as a parameter estimation method to predict the velocity of the telescopic bar during the MCGR distraction process. The system parameters are estimated. by the proposed model. The main purpose is to minimize the error between the actual and desired states by the online configuration of the controller’s parameters. By using online models, we can continuously update and refine system parameters to improve prediction accuracy.
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    PublicationOpen Access
    Design of a toolbox for kinematic analysis of jansen's linkage
    (2022-09-01) YILDIRIM, ALPER; Sünkün S., Parlak B. O. , Yıldırım A., Yavaşoğlu H. A.
    Utilizing industrial robots is an efficient method for addressing the labor crisis and advancing industrial technologies. As a result, industrial robots are becoming increasingly popular. Additionally, the widespread use of industrial robots will increase the interest in robot propulsion mechanisms. Legged robots should be primarily investigated because of their potential advantages. Among leg mechanisms, Jansen\"s linkage (JL) has gained popularity due to its organic walking motion, scalable design, and simple drive by rotary input. However, the highly nonlinear nature of JL makes its analysis challenging. The research provides a user-friendly toolbox design that visualizes the toe trajectory and simultaneously calculates the step height by performing a kinematic analysis of the JL using the user-supplied link lengths. In this way, the study contributes significantly to the design phase of legged robots and reduces the amount of time required.
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    PublicationOpen Access
    Investigation of UWB-IMU sensor fusion for indoor navigation with DoE
    (2023-01-01) DEMİR, UĞUR; AKGÜN, GAZİ; YILDIRIM, ALPER; Durmus S., DEMİR U., AKGÜN G., YILDIRIM A.
    This study presents an evaluation of the optimal parameter configuration for Ultra-Wide Band (UWB) - Inertial Measurement Units - (IMU) based sensor fusion for indoor localization in Non-Line-of-Sight (NLOS) environments. The study employs the least squares method to predict position using UWB technology. Subsequently, sensor fusion techniques combining UWB and IMU are employed, utilizing the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) algorithms to enhance position estimation. To mitigate the effects of noise in IMU data, a high-pass filter is applied before feeding the data into the EKF and UKF. The experimental findings are then evaluated using Design of Experiment (DoE) techniques, and the optimal parameter configurations are analysed using linear regression. This study provides insight into the parameter settings that yield improved accuracy and robustness in UWB-IMU sensor fusion for indoor localization in NLOS scenarios.
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    PublicationOpen Access
    EMG sinyallerinin derin öğrenme ile hareket sınıflandırması
    (2022-09-18) AKGÜN, GAZİ; YILDIRIM, ALPER; DEMİR, UĞUR; KAPLANOĞLU, ERKAN; Akgün G., Yıldırım A., Demir U., Kaplanoğlu E.
    Bu çalışmada EMG sinyalleri üzerinde öznitelikler hesaplanmıştır. Bu öznitelikler ile el hareketlerini sınıflandırmak için derin öğrenme algoritmaları kullanılmıştır. Bir zaman serisi olarak toplanan EMG sinyalleri üzerinde zaman alanında hesaplanan öznitelik vektörleri belirli boyutlarda simetrik matrisler olarak kaydedilmiştir. Yeniden oluşturulan ve resim dosyası formatında kaydedilen veri seti ile Evrişimsel Sinir Ağı eğitilmiştir. Bu eğitim sonucunda tüm veriler ile %93, test verileri ile %79 başarı ile hareket sınıflandırması gerçekleştirilmiştir.