Rancang Sistem Pengendali Transisi Take Off To Cruise Pada Uav Vtol Fixed Wing Menggunakan Metode Fuzzy Logic
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Institusion
Institut Teknologi Sepuluh Nopember
Author
Roosydi, Syahrizal Faried
Subject
TL776 .N67 Quadrotor helicopters--Automatic control
Datestamp
2023-07-30 13:53:17
Abstract :
Unmanned Aerial Vehicle (UAV) secara umum adalah robot terbang yang dikendalikan dari jarak jauh atau tidak dikendarai oleh siapapun dan dapat mengendalikan dirinya sendiri. (UAVs) dibagi menjadi dua berdasarkan bentuk sayap yaitu sayap tetap dan multi-propeller. Seiring perkembangan jaman, dikembangkan UAV tipe hybrid yang menggabungkan kedua tipe tersebut yaitu VTOL Fixed wing. Pada VTOL Fixed wing terdapat 3 mode penerbangan yaitu mode multicopter, transisi, dan fixed wing. Mode penerbangan transisi merupakan perubahan mode multicopter menjadi fixed wing atau sebaliknya. Dalam proses ini kecepatan transisi perlu dipertimbangkan. Oleh karena itu dalam VTOL Fixed wing mode transisi adalah yang paling sulit diantara mode lainnya sehingga membutuhkan sistem kendali yang dapat melakukan transisi. Sistem Kendali transisi pada penelitian ini menggunakan sistem logika fuzzy. Sistem pengendalian transisi pada UAV VTOL Fixed wing dengan menggunakan fuzzy logic dirancang dengan menggunakan pengujian membership function dari fuzzy logic controller untuk mengendalikan setiap aktuator dalam UAV VTOL fixed wing. Fuzzy Logic Controller digunakan untuk mengendalikan attitude, altitude pada mode quadcopter serta elevator, rudder, dan aileron pada mode fixed wing. Jenis fuzzy sets yang digunakan untuk tiap-tiap aktuator berupa bentuk triangular dan trapezoidal. Pada pengujian simulasi, UAV dapat terbang mengikuti waypoint dan melakukan transisi tanpa penurunan altitude pada kondisi tanpa gangguan dan terjadi penurunan altitude sebesar 0.7 m pada kondisi gangguan angin. Hasil performansi dari simulasi sistem kendali Fuzzy Logic menunjukan steady state error sebesar kurang dari 5%. Nilai MAE masing-masing kondisi yaitu, pitch sebesar 0.1045, yaw sebesar 0, roll sebesar 0, dan altitude sebesar 0.5681 dan pada keadaan gangguan angin Nilai MAE masing-masing pitch sebesar 0.1744, yaw sebesar 0.0240, roll sebesar 0.001, dan altitude sebesar 0.7669. Nilai IAE pada keadaan tanpa gangguan masing-masing kondisi yaitu, pitch sebesar 6.2685, yaw sebesar 0, roll sebesar 0, dan altitude sebesar 34.086 kemudian nilai IAE pada keadaan tanpa gangguan masing-masing kondisi yaitu, pitch sebesar 10.707, yaw sebesar 1.440, roll sebesar 0.02692, dan altitude sebesar 46.019. Berdasarkan hasil yang didapat terlihat bahwa fuzzy logic controller mengungguli controller LQR sebesar 0.04 jika dibandingkan dengan penelitian sebelummnya walaupun belum bisa mengungguli kontroller LQR dengan menggunakan Perturbation Observer Gain. ===================================================================================================================================== Unmanned Aerial Vehicles (UAVs) in general are remote-controlled or autonomous flying robots. They are not piloted by any person and can navigate on their own. UAVs are divided into two categories based on their wing configuration: fixed-wing and multi-propeller. Over time, hybrid UAVs have been developed that combine both types, known as VTOL Fixed Wing. In VTOL Fixed Wing UAVs, there are three flight modes: multicopter mode, transition mode, and fixed-wing mode. The transition mode involves switching between multicopter and fixed-wing modes. In this process, the transition speed needs to be considered. Therefore, there is a need for discussion on the transition flight mode, as it is the most challenging among the other modes. Hence, UAVs require a control system capable of executing transitions. In this study, a transition control system is developed using fuzzy logic. The transition control system for VTOL Fixed Wing UAVs employs a fuzzy logic controller that utilizes membership function testing to control each aktuator in the UAV. The fuzzy logic controller is used to control the attitude and altitude in quadcopter mode, as well as the elevator, rudder, and aileron in fixed-wing mode. Triangular and trapezoidal fuzzy sets are used for each aktuator. Through simulation testing, the UAV is capable of flying along waypoints and executing transitions without experiencing altitude drops under normal conditions. However, during windy conditions, a decrease in altitude of 0.7 m occurs. The performance results of the fuzzy logic control system simulation show a steady-state error of less than 5% under both normal and windy conditions. The Mean Absolute Error (MAE) values for each condition are as follows: pitch is 0.1045, yaw is 0, roll is 0, and altitude is 0.5681 under normal conditions; and pitch is 0.1744, yaw is 0.0240, roll is 0.001, and altitude is 0.7669 under windy conditions. The Integral of Absolute Error (IAE) values under normal conditions are: pitch is 6.2685, yaw is 0, roll is 0, and altitude - 34.086. Under windy conditions, the IAE values are: pitch is 10.707, yaw is 1.440, roll is 0.02692, and altitude is 46.019. Based on the obtained results, it can be observed that the fuzzy logic controller outperforms the LQR controller by 0.04 when compared to previous research, although it has
Unmanned Aerial Vehicle (UAV) secara umum adalah robot terbang yang dikendalikan dari jarak jauh atau tidak dikendarai oleh siapapun dan dapat mengendalikan dirinya sendiri. (UAVs) dibagi menjadi dua berdasarkan bentuk sayap yaitu sayap tetap dan multi-propeller. Seiring perkembangan jaman, dikembangkan UAV tipe hybrid yang menggabungkan kedua tipe tersebut yaitu VTOL Fixed wing. Pada VTOL Fixed wing terdapat 3 mode penerbangan yaitu mode multicopter, transisi, dan fixed wing. Mode penerbangan transisi merupakan perubahan mode multicopter menjadi fixed wing atau sebaliknya. Dalam proses ini kecepatan transisi perlu dipertimbangkan. Oleh karena itu dalam VTOL Fixed wing mode transisi adalah yang paling sulit diantara mode lainnya sehingga membutuhkan sistem kendali yang dapat melakukan transisi. Sistem Kendali transisi pada penelitian ini menggunakan sistem logika fuzzy. Sistem pengendalian transisi pada UAV VTOL Fixed wing dengan menggunakan fuzzy logic dirancang dengan menggunakan pengujian membership function dari fuzzy logic controller untuk mengendalikan setiap aktuator dalam UAV VTOL fixed wing. Fuzzy Logic Controller digunakan untuk mengendalikan attitude, altitude pada mode quadcopter serta elevator, rudder, dan aileron pada mode fixed wing. Jenis fuzzy sets yang digunakan untuk tiap-tiap aktuator berupa bentuk triangular dan trapezoidal. Pada pengujian simulasi, UAV dapat terbang mengikuti waypoint dan melakukan transisi tanpa penurunan altitude pada kondisi tanpa gangguan dan terjadi penurunan altitude sebesar 0.7 m pada kondisi gangguan angin. Hasil performansi dari simulasi sistem kendali Fuzzy Logic menunjukan steady state error sebesar kurang dari 5%. Nilai MAE masing-masing kondisi yaitu, pitch sebesar 0.1045, yaw sebesar 0, roll sebesar 0, dan altitude sebesar 0.5681 dan pada keadaan gangguan angin Nilai MAE masing-masing pitch sebesar 0.1744, yaw sebesar 0.0240, roll sebesar 0.001, dan altitude sebesar 0.7669. Nilai IAE pada keadaan tanpa gangguan masing-masing kondisi yaitu, pitch sebesar 6.2685, yaw sebesar 0, roll sebesar 0, dan altitude sebesar 34.086 kemudian nilai IAE pada keadaan tanpa gangguan masing-masing kondisi yaitu, pitch sebesar 10.707, yaw sebesar 1.440, roll sebesar 0.02692, dan altitude sebesar 46.019. Berdasarkan hasil yang didapat terlihat bahwa fuzzy logic controller mengungguli controller LQR sebesar 0.04 jika dibandingkan dengan penelitian sebelummnya walaupun belum bisa mengungguli kontroller LQR dengan menggunakan Perturbation Observer Gain. ===================================================================================================================================== Unmanned Aerial Vehicles (UAVs) in general are remote-controlled or autonomous flying robots. They are not piloted by any person and can navigate on their own. UAVs are divided into two categories based on their wing configuration: fixed-wing and multi-propeller. Over time, hybrid UAVs have been developed that combine both types, known as VTOL Fixed Wing. In VTOL Fixed Wing UAVs, there are three flight modes: multicopter mode, transition mode, and fixed-wing mode. The transition mode involves switching between multicopter and fixed-wing modes. In this process, the transition speed needs to be considered. Therefore, there is a need for discussion on the transition flight mode, as it is the most challenging among the other modes. Hence, UAVs require a control system capable of executing transitions. In this study, a transition control system is developed using fuzzy logic. The transition control system for VTOL Fixed Wing UAVs employs a fuzzy logic controller that utilizes membership function testing to control each aktuator in the UAV. The fuzzy logic controller is used to control the attitude and altitude in quadcopter mode, as well as the elevator, rudder, and aileron in fixed-wing mode. Triangular and trapezoidal fuzzy sets are used for each aktuator. Through simulation testing, the UAV is capable of flying along waypoints and executing transitions without experiencing altitude drops under normal conditions. However, during windy conditions, a decrease in altitude of 0.7 m occurs. The performance results of the fuzzy logic control system simulation show a steady-state error of less than 5% under both normal and windy conditions. The Mean Absolute Error (MAE) values for each condition are as follows: pitch is 0.1045, yaw is 0, roll is 0, and altitude is 0.5681 under normal conditions; and pitch is 0.1744, yaw is 0.0240, roll is 0.001, and altitude is 0.7669 under windy conditions. The Integral of Absolute Error (IAE) values under normal conditions are: pitch is 6.2685, yaw is 0, roll is 0, and altitude - 34.086. Under windy conditions, the IAE values are: pitch is 10.707, yaw is 1.440, roll is 0.02692, and altitude is 46.019. Based on the obtained results, it can be observed that the fuzzy logic controller outperforms the LQR controller by 0.04 when compared to previous research, although it has
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