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Öğe Application of Reservoir Computers for Chaos Synchronization and Cracking Chaos-Based Cryptography in Fermionic 2D Thirring and 4D Gursey Models with Spinor Fields(World Scientific Publ Co Pte Ltd, 2025) Oniz, Yesim; Tosyali, Eren; Aydogmus, FatmaReservoir computers have recently become one of the most widely exploited model-free approaches to chaos synchronization due to their fast convergence speed and simple yet effective learning rules. In this study, reservoir computing has been utilized to emulate the dynamics of chaotic Thirring and Gursey systems. In the supervised learning of the reservoir, one-step ahead states of the dynamical systems have been employed as the teaching signals. After the training phase, the reservoir was first run autonomously and then weakly driven by chaotic systems. It has been shown that the trained reservoir computers can exhibit the same characteristics as the attractors of the learned chaotic systems, which enable their use in synchronization tasks of chaotic systems with possible application in cracking chaos-based cryptography. To investigate the effect of noise on the performance of reservoir computers, noise signals with different colors and amplitudes have been included in the transmitted signals. The obtained results indicate that the proposed scheme can provide lower error metrics for both models.Öğe Chaotic Dynamics and Analysis with Artificial Neural Networks of Aftershocks of 2019 Silivri Earthquake(2024) Aydogmus, Fatma; Oniz, Yesim; Simuratli, Eljan; Tosyalı, Eren; Kaplanvural, Ismaıl; Mutlu, Ahu Kömeç; Önem, Zeynep ÇiçekEarthquakes, whose physical, economic, psychological, and social damages can last for many years, are of vital importance for Türkiye, which is located in the most active earthquake zone that causes many earthquakes in the world. The North Anatolian Fault (NAF) is one of Türkiye's most important tectonic elements as it is the world’s fastest-moving right-lateral and strike-slip active fault zone consisting of many segments. The recent 5.8 magnitude 2019 Silivri earthquake, which occurred in the part of the NAF zone crossing the Marmara Sea, is an indicator that earthquake activity continues in the region. Aftershocks play a crucial role in seismicity research and seismic hazard assessments in terms of providing data and usable information in the examination of seismic dynamics with the changes observed in their time-dependent behavior and regional distribution. In this study, the aftershocks of the Silivri earthquake were examined as a natural laboratory using nonlinear analysis methods. Within the scope of the study, aftershocks of the Silivri earthquake were analyzed with a hybrid artificial neural network as well as different neural network structures, and for this purpose, data from 361 aftershocks with a magnitude greater than 1.5 in the year following the earthquake were used.Öğe Design and Manufacture of a Low-Cost Soft Gripper for Industrial Applications(Ieee, 2025) Akar, Murat; Mura, Bengusu; Oniz, YesimNumber of soft grippers have been developed using smart materials, pneumatic actuators, tendon-style bio-inspired structures. This paper presents a cost-effective fabrication technique for a soft gripper that can grip a wide variety of objects of different weights, sizes, shapes, textures, and stiffness.The gripper features a unique internal structure that enhances performance and adaptability. The primary goal of this study was to develop a robust, affordable, easy to manufacture, and efficient design that can be integrated into various industries that includes food processing, electronics, and glass handling. The manufactured soft gripper in this study, made from RTV-2 (Which has an FDA Approved variation with very close intrinsic properties) silicone, eliminates the need for complex joints and moving parts, reducing hygiene related bacterial risk and simplifying cleaning and maintaining process. The developed gripper has been mounted on a KUKA KR Agilus Sixx industrial robot, and its performance has been validated experimentally for various objects. This research demonstrates effective manufacturing techniques and the potential of soft robotic grippers in industrial applications where traditional rigid grippers may be ineffective.Öğe Direct Model Reference Adaptive Fuzzy Control of Networked SISO Nonlinear Systems(IEEE-Inst Electrical Electronics Engineers Inc, 2016) Khanesar, Mojtaba Ahmadieh; Oniz, Yesim; Kaynak, Okyay; Gao, HuijunThis study presents a novel direct model reference fuzzy controller as applied to the control of a nonlinear system over a network subject to variable network induced time delay. The proposed method uses Pade approximation to cope with this condition. Unlike most approaches seen in the literature, which are mostly model based and necessitate the solution of a set of linear matrix inequalities, the proposed approach is online and can be applied to nonlinear systems with a little knowledge about the structure of the system and the values of its parameters. The stability of the proposed method is proved using an appropriate Lyapunov function. The approach is implemented and tested on a dc motor with nonlinear characteristics and nonlinear state-dependent disturbance. It is shown that it is capable of controlling the system over a network subject to variable network-induced time delay with bounded tracking error. In addition, the effect of packet losses is considered in the implementation part and it is seen that the system can be controlled under these conditions too.Öğe Real-Time Long-Range Control of an Autonomous UAV Using 4G LTE Network(Mdpi, 2025) Mohamed, Mohamed Ahmed Mahrous; Oniz, YesimHighlights What are the main findings? The proposed UAV control system entailing a 4G LTE network and a cloud server was capable of maintaining a stable connection over a long distance of approximately 4200 km (Operator -> Ground Control Station -> UAV). The system provided seamless control and clear video streaming with an average latency of less than 150 ms during flight tests conducted under normal LTE capacity and internet load conditions. What are the implications of the main findings? This study shows that commercial 4G LTE networks can be used for long-range UAV flight operations without needing special or expensive equipment. This setup can be even more effective in UAV applications when operated with 5G/6G networks or satellite connections.Highlights What are the main findings? The proposed UAV control system entailing a 4G LTE network and a cloud server was capable of maintaining a stable connection over a long distance of approximately 4200 km (Operator -> Ground Control Station -> UAV). The system provided seamless control and clear video streaming with an average latency of less than 150 ms during flight tests conducted under normal LTE capacity and internet load conditions. What are the implications of the main findings? This study shows that commercial 4G LTE networks can be used for long-range UAV flight operations without needing special or expensive equipment. This setup can be even more effective in UAV applications when operated with 5G/6G networks or satellite connections.Abstract The operational range and reliability of most commercially available UAVs employed in surveillance, agriculture, and infrastructure inspection missions are limited due to the use of short-range radio frequency connections. To alleviate this issue, the present work investigates the possibility of real-time long-distance UAV control using a commercial 4G LTE network. The proposed system setup consists of a Raspberry Pi 4B as the onboard computer, connected to a Pixhawk-2.4 flight controller mounted on an F450 quadcopter platform. Flight tests were carried out in open-field conditions at altitudes up to 50 m above ground level (AGL). Communication between the UAV and the ground control station is established using TCP and UDP protocols. The flight tests demonstrated stable remote control operation, maintaining an average control delay of under 150 ms and a video quality resolution of 640x480, while the LTE bandwidth ranging from 3 Mbps to 55 Mbps. The farthest recorded test distance of around 4200 km from the UAV to the operator also indicates the capability of LTE systems for beyond-visual-line-of-sight operations. The results show that 4G LTE offers an effective method for extending UAV range at a reasonable cost, but there are limitations in terms of network performance, flight time and regulatory compliance. This study establishes essential groundwork for future UAV operations that will utilize 5G/6G and satellite communication systems.Öğe Simulation and Control of 6-DOF Dynamics for a T-45 UAV Platform(Institute of Electrical and Electronics Engineers Inc., 2025) Mohamed, Mohamed Ahmed Mahrous; Oniz, YesimThis paper presents the development of a 6 degrees of freedom (6DOF) flight dynamics simulation model for the T-45 Goshawk unmanned aerial vehicle (UAV) with a wingspan of 130 cm. The developed model provides a reliable basis for the analysis of UAV performance under normal flight scenarios including hovering and autopilot modes. The aerodynamic coefficients have been determined using Digital DATCOM+pro, a fast and widely adopted tool that relies on empirical and semi-empirical formulations to approximate lift, drag and moment characteristics across different phases of flight. The proposed system architecture integrates the primary physical components, such as atmospheric, propulsion, and control models. MATLAB/Simulink has been utilized to emulate the full motion behavior of the T-45 UAV. The autopilot performance has been tested through multiple scenarios, demonstrating stable and favorable responses. This new approach to simulation offers a way that is adaptable and scalable to the needs of UAV projects and constitutes a software tool for the iterative development and testing of flight control algorithms. © 2025 IEEE.Öğe Tip-2 Nöro-Bulanık Denetleyiciler ile Döner Kanatlı İnsansız Hava Aracının Yörünge Takibi(2024) Oniz, YesimBu çalışmada, tip-2 nöro-bulanık denetleyiciler kullanılarak bir döner kanatlı insansız hava aracının yörünge takibi gerçekleştirilmiştir. Geliştirilen kontrol sisteminin etkinliğini belirlemek amacıyla, oluşturulan iki farklı yörünge için benzetim ve deneysel çalışmalar yapılmıştır. Her bir eksen için farklı bir denetleyici tasarlanmış olup hava aracının yörünge takibi sırasında ilgili eksen için gerçek ve hedef konumları arasındaki fark ve bu değerin zamana göre türevi denetleyicilerin giriş sinyalleri olarak kullanılmıştır. Elde edilen sonuçları daha iyi değerlendirebilmek amacıyla aynı yörüngeler için deneysel ve benzetim çalışmaları orantılı-integral-türev (PID) denetleyici ile tekrarlanmış olup denetleyicilerin cevapları karşılaştırılmıştır. Gerçek zamanlı deneysel çalışmalar, Parrot firması tarafından üretilen Ar.Drone 2.0 ile iç mekanda kontrollü bir ortamda gerçekleştirilmiştir. Özellikle deneysel çalışmalardan elde edilen sonuçlar, tip-2 nöro-bulanık denetleyiciler için geliştirilen kayma kipli kontrol tabanlı öğrenme algoritmalarının daha az kalıcı hal hatası ve daha gürbüz sistem cevabı sağladığını göstermektedir.Öğe Trajectory Control of Quadrotors via Spiking Neural Networks(Mdpi, 2024) Oniz, YesimIn this study, a novel control scheme based on spiking neural networks (SNNs) has been proposed to accomplish the trajectory tracking of quadrotor unmanned aerial vehicles (UAVs). The update rules for the network parameters have been derived using the Lyapunov stability theorem. Three different trajectories have been utilized in the simulated and experimental studies to verify the efficacy of the proposed control scheme. The acquired results have been compared with the responses obtained for proportional-integral-derivative (PID) and traditional neural network controllers. Simulated and experimental studies demonstrate that the proposed SNN-based controller is capable of providing better tracking accuracy and robust system response in the presence of disturbing factors.Öğe Trajectory Generation and Control for UAVs Using Quintic PH Curves and Kolmogorov-Arnold Networks (KANs)(Ieee, 2025) Ciftci, Fatma Senguler; Oniz, YesimThis paper presents a novel methodology that utilizes quintic Pythagorean-Hodograph (PH) curves for trajectory generation of unmanned aerial vehicles (UAVs) and Kolmogorov-Arnold Networks (KANs) for tracking problem. PH curves enable exact arc length computation and ensures smooth transitions in positions, velocities, and accelerations throughout the trajectory. The UAV's movements along the generated trajectory are regulated by KAN-based controllers. A separate controller is designed for each axis. We validate through simulations, indicating that a 40% improvement in tracking accuracy can be attained with KANs over conventional multilayer perceptrons (MLPs) under wind disturbances.Öğe Trajectory Tracking of a Quadcopter Using Fuzzy Logic and Neural Network Controllers(IEEE, 2018) Celen, Burak; Oniz, YesimIn this work, the trajectory tracking control of an Unmanned Aerial Vehicle (UAV) has been realised using fuzzy logic and neural network based controllers. Parrot AR.Drone 2.0 has been selected as the test platform. For simulated and real-time experimental studies, a square shaped reference trajectory has been generated, and the discrepancies from this trajectory in x-and y-directions along with their derivatives have been employed as the input signals to the proposed controllers. The update rules for the neural network have been derived based on the variable structure systems theory to enable stable online tuning of the parameters. The obtained results indicate that both fuzzy logic and neural network controllers can be applied effectively to the trajectory tracking of a drone, and particularly neural networks with variable structure systems theory based learning algorithms exhibit a highly robust behaviour against disturbances.Öğe Using Convolutional Neural Networks and Multi Layer Preceptron in Arabic Handwritten Digit Recognition(Institute of Electrical and Electronics Engineers Inc., 2025) Akbulut, Ulas; Oniz, YesimMachine learning techniques are widely used to recognize handwritten words or digits in different applications including check depositing and mobile banking. The main goal of this study is to employ deep learning techniques on a website to make an application that recognizes drawn Arabic digits on a canvas. The performance of the proposed Convolutional Neural Network(CNN) has been compared to the performance of a Multi Layer Perceptron Model(MLP) indicating a better recognition accuracy. To assess the performance of the proposed network two different datasets have been utilized; The widely used MNIST dataset that includes 60000 Arabic Digit images and a custom dataset collected using the developed website in Visual studio. The hyperparameters have been determined empirically. The trained network have been embedded to the generated website with an accuracy of 93.33 percent. © 2025 IEEE.Öğe Wheel Slip Regulation Using Fuzzy Spiking Neural Networks(IEEE, 2016) Oniz, Yesim; Kaynak, OkyayIn this paper, a fuzzy spiking neural network structure is developed for the wheel slip regulation problem of an Antilock Braking System. Sliding mode control theory is utilized in the derivation of the update rules for the neural network's weights as well as the parameters of the fuzzy membership functions. Gaussian membership functions are used to convert the sensor readings into the neural networks inputs and the spike response model is employed to denote the effect of the incoming spikes on the postsynaptic membrane potential. The use of the Lyapunov stability method for the derivation of the parameter update rules leads to a stable system response even in the existence of external disturbances.
