Tracking Trajectory Automated Guided Vehicle Menggunakan Fuzzy Kontroler pada Rute Magnetic Spot

Septyan, Mamat (2019) Tracking Trajectory Automated Guided Vehicle Menggunakan Fuzzy Kontroler pada Rute Magnetic Spot. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Automated Guided Vehicle (AGV) merupakan moda transportasi yang penting dalam industri. Untuk mencapai fleksibilitas dalam menjalankan tugas yang berulang-ulang, dibutuhkan sistem kontrol yang memadai dalam pengaturan transportasi sehingga teknologi ini banyak digunakan sebagai objek penelitian. Salah satu area penelitian yang masih terbuka adalah permasalahan kontrol tracking terutama untuk trajectory referensi dengan perubahan sudut yang besar. Terdapatnya batasan pergerakan untuk AGV dengan nonholonomic constraint mengakibatkan tracking pada nonsmooth trajectory tidak mudah untuk dilakukan. Penelitian ini membahas pengembangan kontroler fuzzy Takagi-Sugeno dan dynamic nonlinear feedback untuk meminimumkan error tracking pada nonsmooth trajectory. Kontroler dirancang berdasarkan fuzzy Takagi-Sugeno model dan Parallel Distributed Compensation (PDC) dengan gain dan matriks stabilitas dihitung menggunakan Linear Matrix Inequality (LMI). Feedback didapatkan dari dua pengukuran sebagai input utama kontroler dan sebagai faktor koreksi. Perhitungan torsi model dinamika AGV diperoleh dari input auxiliary velocity dan dynamic nonlinear feedback. Hasil simulasi menunjukkan kontroler dengan satu pengukuran menghasilkan steady state error tracking dengan nilai settling time kurang dari 15 s pada semua trajectory referensi kecuali untuk error orientasi dimana nilai settling time sebesar 31 s karena di setiap titik belokan terjadi overshoot. Namun dengan menggunakan dua pengukuran dihasilkan steady state error dengan nilai settling time kurang dari 12 s pada semua trajectory referensi. ================================================================================================ Automated Guided Vehicle (AGV) is an important mode of transportation in the industry. In order to achieve flexibility to deal with repetitive tasks, a sufficient control system is needed in regulating transportation consequently this technology has been widely used as an object of research. One of the research open areas is the problem of a tracking control especially for reference trajectories with big angle changes. The limitation of movement for AGV with a nonholonomic constraints resulting the tracking on nonsmooth trajectory is difficult to apply. This research explores the development of fuzzy Takagi-Sugeno controller and dynamic nonlinear feedback to minimize tracking error on nonsmooth trajectory. The controller is designed based on the Takagi-Sugeno fuzzy model and Parallel Distributed Compensation which its gain and stability matrix is calculated using Linear Matrix Inequality. The feedback gain is obtained from two measurement as the controller’s main input and a correction factor. The calculation of the AGV dynamics model torque is obtained from auxiliary velocity input and dynamic nonlinear feedback. Simulation results show that the controller using one measurement produces steady state tracking error with settling times value less than 15 s in all reference trajectories except for orientation errors where the settling time value is 31 s because overshoot occurs at each turn point. However, the controller using two measurement produces steady state error with settling times value less than 12 s in all reference trajectories

Item Type: Thesis (Masters)
Additional Information: RTE 629.89 Sep t-1 2019
Uncontrolled Keywords: AGV, kontrol fuzzy, encoder, sensor magnetik, transportasi
Subjects: Q Science > QA Mathematics > QA9.64 Fuzzy logic
T Technology > TJ Mechanical engineering and machinery > TJ223 PID controllers
T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7872 Electromagnetic Devices
T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL521.3 Automatic Control
Divisions: Faculty of Electrical Technology > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User: Mamat Septyan
Date Deposited: 14 Jul 2021 03:55
Last Modified: 14 Jul 2021 03:55
URI: https://repository.its.ac.id/id/eprint/60925

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