Browsing by Author "Aydin, Gulsah Demirhan"

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    Lyapunov-Based Controller Design for Precise Monitoring, Speed Control and Trajectory Planning in Autonomous Tractors With Trailers
    (Ieee, 2024) Aydin, Gulsah Demirhan; Dogan, Deren; Turken, Yusuf Tugberk; Mechatronics Engineering; 15. Graduate School of Natural and Applied Sciences; 06. School Of Engineering; 01. Atılım University
    Nowadays, modern technology-based agriculture operations are replacing traditional farming practices. Smart agricultural systems have gained popularity as a result of the demand for more productive and environmentally friendly farming methods. Consequently, the agricultural sector continues to be one of the driving forces behind automation, viewing technological advancements as a means of increasing productivity while lowering costs. Automation in agriculture ranges from tractors built with apparatus that can carry out complicated tasks on their own to cultivation surveillance. This study aims to optimize the speed of an autonomous tractor through a dynamic code based on Lyapunov control method as an innovative approach in smart agriculture. Beyond speed optimization, the research also addresses practical challenges encountered in real-world scenarios, including obstacles such as living entities. By evaluating the potential of Lyapunov control methodology in the effective management of agricultural machinery, this work offers an innovative perspective on smart agricultural technologies.
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    A New Approach for Addressing Slip Ratio Optimization and Trajectory Tracking Challenges in Autonomous Tractor Operations
    (Ieee, 2024) Aydin, Gulsah Demirhan; Aydemir, Ali Bahadir; Kansou, Mohamad Thaer; Altinuc, Kemal Orcun; Mechatronics Engineering; Mechatronics Engineering; 15. Graduate School of Natural and Applied Sciences; 06. School Of Engineering; 01. Atılım University
    The usage of autonomous agricultural machines is increasing. In this study, two controllers have been designed for trajectory following and longitudinal tire slip ratio control of a rear-wheel independent traction electric autonomous tractor. The first controller is model predictive control (MPC) and the second controller is proportional integral derivative (PID) based. To evaluate the performance of the controllers in the simulation environment, a mathematical tractor model is prepared. Simulations have been made and performances of the designed controllers are shared.