Pengimplementasian Navigasi Berbasis Proportional–Integral–Derivative (PID) Pada Autonomous Underwater Vehicle

Riyadi, Mohammad Firman (2024) Pengimplementasian Navigasi Berbasis Proportional–Integral–Derivative (PID) Pada Autonomous Underwater Vehicle. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Sinyal GPS tidak dapat menembus beberapa tempat diantaranya bunker , ruangan tertutup, hutan ataupun bawah permukaan air. Oleh karena itu diperlukan navigasi tanpa GPS dengan metode dead reckoning. Metode navigasi berbasis PID saya terapkan pada AUV (Autonomous Underwater Vehicle) Sensor IMU saat dalam air mengalami drifting yang sangat tinggi sehingga memerlukan suatu filter yaitu Kalman Filter untuk mereduksi hal tersebut. Pada penelitian ini Kalman Filter dikombinasikan dengan metode PID untuk stabilitas robot. Robot sudah mengikuti jalur, namun masih kurang akurat. Pengujian kontrol navigasi PID pada robot menunjukkan bahwa metode ini dapat mengurangi deviasi robot dari jalur yang ditentukan. Dalam pengujian pergerakan maju, ke kanan, dan mundur, rata-rata total penyimpangan antara jalur yang dilalui robot dengan jalur sesungguhnya tanpa PID adalah 38,75 pixel atau 11,22 cm, sementara dengan PID adalah 17,98 pixel atau 5,1 cm. Penyimpangan berhasil dikurangi sebesar 20,77 pixel atau 53,57% dari penyimpangan awal. Dalam pengujian pergerakan maju, ke kiri, dan mundur, rata-rata total penyimpangan antara jalur yang dilalui robot dengan jalur sesungguhnya tanpa PID adalah 31,51 pixel atau 9,6 cm, sedangkan dengan PID adalah 25,78 pixel atau 7,13 cm. Penyimpangan yang berhasil dikurangi sebesar 5,73 pixel atau 18,17% dari penyimpangan awal.
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GPS signals cannot penetrate several places including bunkers, closed rooms, forests or under the water surface. Therefore, navigation without GPS is required with the dead reckoning method. I applied navigation bases on PID to the AUV (Autonomous Underwater Vehicle) IMU sensor when in water experiences very high drifting so it requires a filter, namely the Kalman Filter to reduce this. In this research, Kalman Filter is combined with PID method for robot stability. Robots that have been with the PID method when compared to those without PID have fewer errors in following the path.The results of PID navigation control testing on a robot show that this method can reduce the robot’s deviation from the specified path. In the forward, right, and backward movement tests, the average total deviation between the path traveled by the robot and the actual path without PID was 38.75 pixels or 11.22 cm, while with PID it was 17.98 pixels or 5.1 cm. The deviation was reduced by 20.77 pixels or 53.57% of the initial deviation. In the forward, left, and backward movement tests, the average total deviation between the path traveled by the robot and the actual path without PID was 31.51 pixels or 9.6 cm, while with PID it was 25.78 pixels or 7.13 cm. The deviation that was successfully reduced was 5.73 pixels or 18.17% of the initial deviation.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Autonomous Underwater Vehicle, Kalman Filter, Filter Kalman, PID
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ211 Robotics. T Technology > TJ Mechanical engineering and machinery > TJ211.4 Robot motion T Technology > TJ Mechanical engineering and machinery > TJ223 PID controllers
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User:	Mohammad Firman Riyadi
Date Deposited:	12 Feb 2024 01:27
Last Modified:	12 Feb 2024 01:27
URI:	http://repository.its.ac.id/id/eprint/106780

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