Yazar "Celik, Orkan Murat" seçeneğine göre listele

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    Design of a smart glove for monitoring finger injury rehabilitation process via MQTT server
    (Ieee, 2018) Koseoglu, Murat; Celik, Orkan Murat; Pektas, Omer
    In this paper, a wearable glove, which measures hand parameters such as finger angle and force experienced by the finger, was designed by considering four fingers. The hand parameters were measured by using flexible resistive sensors and resistive force sensors. The obtained data were published to Message Queuing Telemetry Transport (MQTT) server via Esp8266 Wi-Fi module. MQTT is a machine to machine (M2M)/Internet of Things connectivity protocol. Then an interface for the application was designed on Visual Studio and the meaningful data were presented to the user and physician. This application receives the data from Mosquitto broker service that uses MQTT protocol, thus the changes in the data can be seen from progress bars on the application form readily, and the rehabilitation process can be monitored by the physician remotely.
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    Design of an Autonomous Mobile Robot Based on ROS
    (Ieee, 2017) Koseoglu, Murat; Celik, Orkan Murat; Pektas, Omer
    In this paper, design of an autonomous mobile robot (AMR) adapted for robot operating system (ROS) is presented by considering both the hardware architecture and electronic communication protocols. Initially the purpose of the robot has been determined, and then the required components to construct the robot have been obtained. After mounting the electronic and mechanic hardware components on the platform, the required interconnections, data exchange system and software have been installed. Then the required tests have been run on the platform and some solutions methods have been proposed for the problems encountered during the tests. The results obtained and experience gained in the design of the platform have been quite satisfactory and will be a guiding light for future works.
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    Design of Hybrid MPC-PID Controller Based on Fractional Order Model of AMR
    (Ieee-Inst Electrical Electronics Engineers Inc, 2025) Celik, Orkan Murat; Deniz, Furkan Nur; Koseoglu, Murat
    In today's world, robots, especially autonomous mobile robots (AMR), have critical roles in domestic, medical, and industrial applications. As technology develops and the diverse demands emerge, the tasks to be completed by AMRs become more complex and challenging. AMRs need to be improved to struggle with these difficulties. So, implementing more precise and reliable control strategies for robots is becoming increasingly important. To this end, a novel hybrid control methodology, composed of a Proportional-Integral-Derivative (PID) controller and a model predictive controller (MPC), is proposed based on the fractional-order model of the AMR. The MPC optimizes the reference signal for the PID controller, enhancing overall performance. First, the fractional order model of AMR is extracted by considering the input and output data from AMR at different velocity values, eliminating the need for detailed physical modeling and technical information for AMR. After verifying the obtained model, a model reduction technique is applied to simplify the obtained transfer function to reduce the computational burden on the processor of AMR. Then, based on the simplified transfer function a hybrid MPC-PID controller is designed and implemented on Turtlebot3 Burger (TB3) AMR to improve the robot's performance. It is demonstrated that the hybrid controller, which is designed without requiring detailed equations of the system components, exhibits a good performance in minimizing errors and enhancing reliability for both angular and linear velocity values.
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    Experimental performance analysis of an AMR controlled by a hybrid MPC-PID method
    (Polska Akad Nauk, Polish Acad Sci, Div Iv Technical Sciences Pas, 2026) Celik, Orkan Murat; Koseoglu, Murat; Deniz, Furkan Nur
    Recent advances in decision-making algorithms used in mobile robotics require more advanced and adaptive control strategies. Model predictive control (MPC) is one of the prominent strategies to manage diverse kinds of complex dynamic systems. Despite their widespread adoption in industrial robotics owing to their structural simplicity and ease of implementation, proportional-integral-derivative (PID) controllers exhibit notable limitations in effectively addressing process variations and system constraints, particularly those arising from mechanical constraints on joint positions and velocities. As autonomous mobile robots (AMRs) have been increasingly deployed in various and demanding applications, the need for more advanced control algorithms has become critical. In this study, a novel hybrid control framework integrating MPC and PID strategies is proposed and experimentally validated on a real-world differential drive robot, aiming to enhance tracking accuracy and overall operational performance. The system model of the TurtleBot3 robot is identified using the System Identification Toolbox and validated through extensive motion tests on the real robot by using Robot Operating System 2. The proposed control scheme combines the predictive capabilities of MPC with the reactive nature of PID to facilitate improved management of system constraints, aiming to improve the performance of AMR in controlling both linear and angular velocities. Experimental results show that the hybrid MPC-PID controller exhibits better performance by reducing tracking errors while maintaining reliability and robustness characteristics over a conventional PID controller. These results demonstrate that the hybrid MPC-PID approach provides a more effective solution for dynamic control tasks in mobile robotic systems, particularly in scenarios requiring high accuracy and reliability.
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    Improvement of Frequency Responses of MSBL-Based Approximate Fractional-Order Derivative Operator and Its Digital Realization with FPGA
    (Mdpi, 2025) Pektas, Omer; Celik, Orkan Murat; Koseoglu, Murat
    Fractional calculus has emerged as an important research area for the analysis and solution of complex engineering problems. However, because exact implementation of fractional-order (FO) operators is not possible, various integer-order approximations are used for implementation. Agreement of the time and frequency responses obtained with these approximation methods with the analytical responses of the FO models is critical for application accuracy and performance. This study aims to reduce the difference between analytical and approximation-based frequency responses through optimization for better implementation performance. After the success of the proposed method was proved for an FO operator, it was applied to an FOPID controller and an FO filter. Notable improvements were observed in both frequency and time response. To test the practicality of the method, the proposed method and other approximation methods were tested on an FPGA using the Vitis Model Composer Hub system generator block within the MATLAB Simulink environment. Also, the proposed method was experimentally implemented for an FO operator on a Nexys 4 DDR Artix-7 FPGA. It was observed that FPGA implementation and simulation results were in good agreement with each other.
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    System Identification Based Fractional Order Plant Realization on an FPGA
    (Institute of Electrical and Electronics Engineers Inc., 2025) Pektas, Omer; Celik, Orkan Murat; Koseoglu, Murat
    The control of actuators for diverse applications is gaining increasing importance across both industrial domains and everyday technologies. Classical control algorithms are progressively being replaced by more advanced and intelligent control methodologies, in parallel with advancements in computational power, particularly in CPUs, GPUs, FPGAs and even MCUs. Traditional approaches, such as Proportional-Integral-Derivative (PID) and Proportional-Integral (PI) controllers, are giving way to data-driven control techniques. These modern methods typically rely on an accurate mathematical model of the plant. Consequently, the fidelity of this model in representing the real system plays a crucial role in the overall performance and reliability of data-driven control strategies. In this study, a fractional-order (FO) system identification process was applied to a real DC motor-driver system to develop a more accurate dynamic model. The identified FO model was validated through various methods to ensure its fidelity to the actual system. To enable efficient implementation, the FO model was approximated by an equivalent integer-order model and subsequently reduced to lower its computational complexity. To evaluate its suitability for embedded control applications, the reduced model was implemented and simulated on an FPGA platform. Comprehensive simulation and experimental analyses, including frequency and step response evaluations, were performed to assess the performance and practicality of the FPGA-based implementation. The results highlight the potential of the proposed approach for real-time control and signal processing applications. © 2025 IEEE.