Fuzzy PD control for a quadrotor with experimental results
Quadrotor is an unmanned aerial vehicle widely used in traffic construction monitoring, volcano monitoring, forest fire, power line inspection, missing person search and disaster relief. The dynamic model of quadrotor becomes complex and non-linear due to four motors with four propellers to control...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | Results in Control and Optimization |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666720725000542 |
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| author | Anh T. Nguyen Nam H. Nguyen Mien L. Trinh |
| author_facet | Anh T. Nguyen Nam H. Nguyen Mien L. Trinh |
| author_sort | Anh T. Nguyen |
| collection | DOAJ |
| description | Quadrotor is an unmanned aerial vehicle widely used in traffic construction monitoring, volcano monitoring, forest fire, power line inspection, missing person search and disaster relief. The dynamic model of quadrotor becomes complex and non-linear due to four motors with four propellers to control and stabilize the motion. One disadvantage of the traditional PID controller is that its parameters are tuned based on trials and errors, but the fuzzy PID controller will automatically adjust its PID gains based on the IF-THEN rules and the parameters of the fuzzy systems are designed beforehand. For other adaptive fuzzy controllers, their parameters are online updated with large computational load. In this paper, we design an intelligent controller to manage the operating state of quadrotor (UAV) by combining the advantages of traditional PD controller with fuzzy logic inference systems to tune its parameters. These Fuzzy PD controllers performs control of the movement of the quadrotor along three axes to follow the desired trajectory. The proposed Fuzzy PD control system for the quadrotor is simulated and evaluated on Matlab-Simulink, then conducted with real-time experiments on QDrone2 physical system. Simulation and experimental results with comparisons to the PD controller have proven the effectiveness of the proposed control method with small tracking error under the impact of time-varying disturbance and additional load. |
| format | Article |
| id | doaj-art-9526535907a349d6b2d8bc6bbb28d72f |
| institution | OA Journals |
| issn | 2666-7207 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Control and Optimization |
| spelling | doaj-art-9526535907a349d6b2d8bc6bbb28d72f2025-08-20T02:35:47ZengElsevierResults in Control and Optimization2666-72072025-06-011910056810.1016/j.rico.2025.100568Fuzzy PD control for a quadrotor with experimental resultsAnh T. Nguyen0Nam H. Nguyen1Mien L. Trinh2Department of Automation Engineering, School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, No. 1, Dai Co Viet Street, Hanoi, 11615, Viet NamDepartment of Automation Engineering, School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, No. 1, Dai Co Viet Street, Hanoi, 11615, Viet Nam; Corresponding authors.University of Transport and Communications, No. 3 Cau Giay Street, Lang Thuong Ward, Dong Da District, 11512 Hanoi, Viet Nam; Corresponding authors.Quadrotor is an unmanned aerial vehicle widely used in traffic construction monitoring, volcano monitoring, forest fire, power line inspection, missing person search and disaster relief. The dynamic model of quadrotor becomes complex and non-linear due to four motors with four propellers to control and stabilize the motion. One disadvantage of the traditional PID controller is that its parameters are tuned based on trials and errors, but the fuzzy PID controller will automatically adjust its PID gains based on the IF-THEN rules and the parameters of the fuzzy systems are designed beforehand. For other adaptive fuzzy controllers, their parameters are online updated with large computational load. In this paper, we design an intelligent controller to manage the operating state of quadrotor (UAV) by combining the advantages of traditional PD controller with fuzzy logic inference systems to tune its parameters. These Fuzzy PD controllers performs control of the movement of the quadrotor along three axes to follow the desired trajectory. The proposed Fuzzy PD control system for the quadrotor is simulated and evaluated on Matlab-Simulink, then conducted with real-time experiments on QDrone2 physical system. Simulation and experimental results with comparisons to the PD controller have proven the effectiveness of the proposed control method with small tracking error under the impact of time-varying disturbance and additional load.http://www.sciencedirect.com/science/article/pii/S2666720725000542Fuzzy logic inference systemPIDQuadrotorTracking controlQuanserOptiTrack system |
| spellingShingle | Anh T. Nguyen Nam H. Nguyen Mien L. Trinh Fuzzy PD control for a quadrotor with experimental results Results in Control and Optimization Fuzzy logic inference system PID Quadrotor Tracking control Quanser OptiTrack system |
| title | Fuzzy PD control for a quadrotor with experimental results |
| title_full | Fuzzy PD control for a quadrotor with experimental results |
| title_fullStr | Fuzzy PD control for a quadrotor with experimental results |
| title_full_unstemmed | Fuzzy PD control for a quadrotor with experimental results |
| title_short | Fuzzy PD control for a quadrotor with experimental results |
| title_sort | fuzzy pd control for a quadrotor with experimental results |
| topic | Fuzzy logic inference system PID Quadrotor Tracking control Quanser OptiTrack system |
| url | http://www.sciencedirect.com/science/article/pii/S2666720725000542 |
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