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PERANCANGAN AUTOPILOT LATERAL-DIREKSIONAL PESAWAT NIRAWAK LSU-05 (THE DESIGN OF THE LATERAL-DIRECTIONAL AUTOPILOT FOR THE LSU-05 UNMANNED AERIAL VEHICLE) Muhammad Fajar; Ony Arifianto
Jurnal Teknologi Dirgantara Vol. 15 No. 2 Desember 2017
Publisher : National Institute of Aeronautics and Space - LAPAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.jtd.2017.v0.a2760

The autopilot on the aircraft is developed based on the mode of motion of the aircraft i.e. longitudinal and lateral-directional motion. In this paper, an autopilot is designed in lateral-directional mode for LSU-05 aircraft. The autopilot is designed at a range of aircraft operating speeds of 15 m/s, 20 m/s, 25 m/s, and 30 m/s at 1000 m altitude. Designed autopilots are Roll Attitude Hold, Heading Hold and Waypoint Following. Autopilot is designed based on linear model in the form of state-space. The controller used is a Proportional-Integral-Derivative (PID) controller. Simulation results show the value of overshoot / undershoot does not exceed 5% and settling time is less than 30 second if given step command. Abstrak Autopilot pada pesawat dikembangkan berdasarkan pada modus gerak pesawat yaitu modus gerak longitudinal dan lateral-directional. Pada makalah ini, dirancang autopilot pada modus gerak lateral-directional untuk pesawat LSU-05. Autopilot dirancang pada range kecepatan operasi pesawat yaitu 15 m/dtk, 20 m/dtk, 25 m/dtk, dan 30 m/dtk dengan ketinggian 1000 m. Autopilot yang dirancang adalah Roll Attitude Hold, Heading Hold dan Waypoint Following. Autopilot dirancang berdasarkan model linier dalam bentuk state-space. Pengendali yang digunakan adalah pengendali Proportional-Integral-Derivative (PID). Hasil simulasi menunjukan nilai overshoot/undershoot tidak melebihi 5% dan settling time kurang dari 30 detik jika diberikan perintah step.

Intelligent Eyes on the Battlefield: Developing an AI-Vision Based Military Vehicle and Infantry Detection System Wibowo, Pasha R A; Ummah , Khairul; Arifianto, Ony; Widagdo, Djarot; Riszal, Akhmad; Arif, Yanuar Zulardiansyah
Journal of Applied Science, Engineering and Technology Vol. 3 No. 2 (2023): December 2023
Publisher : INSTEP Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47355/jaset.v3i2.63

The importance of accurate, real-time intelligence in modern warfare is crucial, especially in reconnaissance and surveillance operations. Currently, drones are widely used for reconnaissance, but generally rely only on the operator's ability to monitor operation targets. This research is aimed at developing an AI vision assistance system to enhance the ability to detect military vehicles and infantry. The method used is computer vision trained to recognize and differentiate several military objects. The YOLO model is used to detect and distinguish objects. To improve detection capabilities, the YOLO v8 model was retrained with an additional dataset sourced from battle recordings on the battlefield. The results show a detection accuracy rate of 95% in detecting vehicles and infantry under normal visual conditions. The model from this research can be used to enhance the capabilities of reconnaissance drones and the effectiveness of monitoring operations.

Intelligent Eyes on the Battlefield: Developing an AI-Vision Based Military Vehicle and Infantry Detection System Wibowo, Pasha R A; Ummah, Khairul; Arifianto, Ony; Widagdo, Djarot; Riszal, Akhmad; Arif, Yanuar Zulardiansyah; Sadono, Mahardi
Jurnal Inovasi Teknologi Vol 5 No 1 (2024): April
Publisher : Engineering Forum of Western Indonesian Government Universities Board (Forum Teknik, BKS-PTN Wilayah Barat) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

The importance of accurate, real-time intelligence in modern warfare is crucial, especially in reconnaissance and surveillance operations. Currently, drones are widely used for reconnaissance, but generally rely only on the operator's ability to monitor operation targets. This research is aimed at developing an AI vision assistance system to enhance the ability to detect military vehicles and infantry. The method used is computer vision trained to recognize and differentiate several military objects. The YOLO model is used to detect and distinguish objects. To improve detection capabilities, the YOLO v8 model was retrained with an additional dataset sourced from battle recordings on the battlefield. The results show a detection accuracy rate of 95% in detecting vehicles and infantry under normal visual conditions. The model from this research can be used to enhance the capabilities of reconnaissance drones and the effectiveness of monitoring operations.

Kinerja Optical Flow dalam Estimasi Kecepatan Terbang SUAV Menggunakan Metode Farneback Aziz Fathurrahman; Ony Arifianto; Yazdi Ibrahim Jenie; Hari Muhammad
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 1: Februari 2025
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i1.15001

This paper evaluates the performance of the Farneback optical flow method for estimating the flight speed of a small unmanned aerial vehicle (SUAV) in a simulated 3D World MATLAB-Unreal Engine environment. Optical flow offers a promising solution for velocity estimation, which is crucial for autonomous navigation. A downward-facing monocular camera model was simulated on an SUAV during steady state, straight flight at 100 m altitude and 25 m/s airspeed. Three simulated flight scenes—forest, city block, and water—representing poor, moderate, and rich textures were used to assess the method’s performance. Results demonstrated that using the median estimate of the optical flow field yielded accurate velocity estimations in moderate to rich texture scenes. Over the city block and forest scenes, mean velocity estimation accuracy was 0.6 m/s (σ = 0.2 m/s) and 0.3 m/s (σ = 0.4 m/s), respectively. The impact of camera tilt angle and altitude variations on estimation accuracy was also investigated. Both factors introduced bias, with accuracy decreasing to 1.7 m/s (σ = 0.2 m/s) and 1.9 m/s (σ = 0.2 m/s) for +10° and -10° camera tilt, respectively. Similarly, altitude differences of +10m and -10m resulted in reduced accuracy of 1.9 m/s (σ = 0.2 m/s) and 4.3 m/s (σ = 0.1 m/s), respectively. This study demonstrates the potential of the Farneback method for determining flight speed under steady, straight flight conditions with acceptable accuracy.

Analisis Risiko Bird Strike dengan Metode Sowden dan Metode MOORA di Bandara Internasional XYZ Nursani, Ima; Arifianto, Ony
Warta Penelitian Perhubungan Vol. 35 No. 2 (2023): Warta Penelitian Perhubungan
Publisher : Sekretariat Badan Penelitian dan Pengembangan Perhubungan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25104/warlit.v35i2.2311

Bandara XYZ merupakan bandara yang memiliki habitat alam yang sangat ramai akan keberadaan satwa liar, terutama burung. Interaksi antara pesawat dan burung dapat menimbulkan berbagai permasalahan, seperti bird strike, perubahan perilaku migrasi, dan ancaman terhadap kelestarian populasi jenis tertentu. Oleh karena itu, pengelolaan satwa liar dan operasional penerbangan merupakan isu yang kompleks dan penting untuk diatasi. Dalam melakukan penilaian risiko, digunakan tiga metode, yaitu metode Sowden di mana penilaian berdasarkan ukuran berat badan burung dan karakteristik sosial, metode MOORA yang merupakan metode penghitungan dengan mempertimbangkan lokasi burung berada, kemampuan terbang burung dan jumlah burung pada saat pengamatan. Berdasarkan analisa penghitungan dengan metode Sowden dan metode MOORA, yang kemudian dibuat analisis lanjutan dengan risk assessment, maka dapat diambil kesimpulan bahwa kemungkinan risiko bird strike di Bandara XYZ sangat tinggi karena beberapa jenis burung, seperti burung kuntul kerbau, cangak abu, cangak merah, dan blekok sawah banyak ditemukan di area airside dan landside. Hal ini ditunjukkan dengan adanya spesies burung yang memiliki skor tingkat bahaya sangat tinggi untuk pada penghitungan dengan kedua metode tersebut. Kemudian jika spesies tersebut mengalami tabrakan dengan pesawat, maka akan mengakibatkan dampak yang signifikan.

Analisis Risiko Bird Strike dengan Metode Sowden dan Metode MOORA di Bandara Internasional XYZ Nursani, Ima; Arifianto, Ony
Warta Penelitian Perhubungan Vol. 35 No. 2 (2023): Warta Penelitian Perhubungan
Publisher : Sekretariat Badan Penelitian dan Pengembangan Perhubungan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25104/warlit.v35i2.2311

Bandara XYZ merupakan bandara yang memiliki habitat alam yang sangat ramai akan keberadaan satwa liar, terutama burung. Interaksi antara pesawat dan burung dapat menimbulkan berbagai permasalahan, seperti bird strike, perubahan perilaku migrasi, dan ancaman terhadap kelestarian populasi jenis tertentu. Oleh karena itu, pengelolaan satwa liar dan operasional penerbangan merupakan isu yang kompleks dan penting untuk diatasi. Dalam melakukan penilaian risiko, digunakan tiga metode, yaitu metode Sowden di mana penilaian berdasarkan ukuran berat badan burung dan karakteristik sosial, metode MOORA yang merupakan metode penghitungan dengan mempertimbangkan lokasi burung berada, kemampuan terbang burung dan jumlah burung pada saat pengamatan. Berdasarkan analisa penghitungan dengan metode Sowden dan metode MOORA, yang kemudian dibuat analisis lanjutan dengan risk assessment, maka dapat diambil kesimpulan bahwa kemungkinan risiko bird strike di Bandara XYZ sangat tinggi karena beberapa jenis burung, seperti burung kuntul kerbau, cangak abu, cangak merah, dan blekok sawah banyak ditemukan di area airside dan landside. Hal ini ditunjukkan dengan adanya spesies burung yang memiliki skor tingkat bahaya sangat tinggi untuk pada penghitungan dengan kedua metode tersebut. Kemudian jika spesies tersebut mengalami tabrakan dengan pesawat, maka akan mengakibatkan dampak yang signifikan.

Evaluation of Artificial Neural Networks Technique for Calibration of Five-Hole Probe Measurement Birry, Abdurrahman; Arifianto, Ony; Mulyanto, Taufiq
Indonesian Journal of Aerospace Vol. 22 No. 1 (2024): Indonesian Journal Of Aerospace
Publisher : BRIN Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/ijoa.2024.2784

In the present study, the Artificial Neural Networks (ANN) technique was implemented to predict the flow parameters of a Five-Hole Probe (FHP). The experimental data were obtained from a subsonic open jet wind tunnel at a speed increased from 0 to 1180 rpm in increments of 200 rpm. The ANN approach is carried out in stages, starting with the method of selecting training data and validation, then increasing the number of neurons, varying the correlation between the activation function and the optimizer, and finally finding the optimal number of hidden layers. In the ANN approach, the mean absolute errors of 0.2705, 0.3326, and 1.0748 were achieved for estimating angle α which represents the angle of attack, angle β which represents the angle of sideslip, and speed, respectively. At the end of this study, the results were compared with the rational function approach. It was concluded that the ANN approach was more accurate compared to the rational function based on statistical parameters such as mean absolute error, max absolute error, and coefficient of determination (r2).

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