Research on the Dynamics Model and Jump/Drop Control Strategy of Distributed-Propeller Unmanned Aerial Vehicles
Compared with conventional drones, distributed powered drones have significant advantages in handling stability characteristics, lift and drag characteristics, and takeoff and landing performance. However, there are also challenges such as aerodynamic interference of multi powered slipstream, distri...
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Veröffentlicht in: | Applied sciences 2024-12, Vol.14 (24), p.12040 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Compared with conventional drones, distributed powered drones have significant advantages in handling stability characteristics, lift and drag characteristics, and takeoff and landing performance. However, there are also challenges such as aerodynamic interference of multi powered slipstream, distributed-power/wing strong-coupling dynamic modeling, and redundant control allocation of distributed-power control mechanisms. The paper has carried out the research on the dynamic modeling method, flight dynamics characteristics analysis, and the design of the control strategy of the jump and steep descent of the distributed dynamic configuration fixed wing unmanned aerial vehicle. A comprehensive aircraft dynamic model considering the influence of propeller slip on aerodynamics was established by combining theoretical derivation with flight experiment data correction. By comparing and analyzing the longitudinal and lateral heading control efficiency of unmanned aerial vehicles under rudder deflection and dynamic differential, a control concept of roll co-ordination control yaw combined with left and right dynamic differential is proposed. Digital simulation and flight tests showed that the established full aircraft dynamics model can accurately reflect the motion laws of distributed-power takeoff and landing unmanned aerial vehicles. The designed takeoff and landing strategy and control scheme can successfully achieve unmanned aerial vehicle takeoff and landing and perform cruising flight tasks. |
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ISSN: | 2076-3417 2076-3417 |
DOI: | 10.3390/app142412040 |