Conference Paper
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Year 2023, Volume: 23, 413 - 419, 30.09.2023
https://doi.org/10.55549/epstem.1371783

Abstract

References

  • Alanezi, M. A., Haruna, Z., Sha’aban, Y. A., Bouchekara, H. R. E. H., Nahas, M., & Shahriar, M. S. (2022). Obstacle avoidance-based autonomous navigation of a quadrotor system. Drones, 6(10), 1–19. https://doi.org/10.3390/drones6100288
  • Coban, S., Bilgic, H. H., & Akan, E. (2020). Improving autonomous performance of a passive morphing fixed wing UAV. Information Technology and Control, 49(1), 28–35. https://doi.org/10.5755/j01.itc.49.1.23275
  • Falanga, D., Kleber, K., Mintchev, S., Floreano, D., & Scaramuzza, D. (2019). The Foldable Drone: A Morphing Quadrotor That Can Squeeze and Fly. IEEE Robotics and Automation Letters, 4(2), 209–216. https://doi.org/10.1109/LRA.2018.2885575

Stochastic Longitudinal Autopilot Tuning for Best Autonomous Flight Performance of a Morphing VTOL Drone

Year 2023, Volume: 23, 413 - 419, 30.09.2023
https://doi.org/10.55549/epstem.1371783

Abstract

In this conference paper autonomous flight performance maximization of a morphing vertical take-off and landing (i.e., VTOL) drone is considered by using stochastic optimization approach. For flight control system a PID based hierarchical control system is applied. In this paper PID controller which is used for pitch angle is considered. In this research only longitudinal flight and longitudinal control system is evaluated during aircraft mode where the pitch motion is in primary interest and the used control surface is the elevator of VTOL drone. For optimization approach simultaneous perturbation stochastic approximation (i.e., SPSA) is chosen. It is fast and safe in stochastic optimization problems when it is not possible to evaluate gradient analytically. At the end of this paper a cost function consisting terms such that settling time, rise time and overshoot is minimized. A detailed graphical analysis is made in order to better evaluate effect of morphing on longitudinal flight of a morphing vertical take-off and landing drone flight. Moreover, the cost function consists of rise time, settling time, and overshoot during trajectory tracking.

References

  • Alanezi, M. A., Haruna, Z., Sha’aban, Y. A., Bouchekara, H. R. E. H., Nahas, M., & Shahriar, M. S. (2022). Obstacle avoidance-based autonomous navigation of a quadrotor system. Drones, 6(10), 1–19. https://doi.org/10.3390/drones6100288
  • Coban, S., Bilgic, H. H., & Akan, E. (2020). Improving autonomous performance of a passive morphing fixed wing UAV. Information Technology and Control, 49(1), 28–35. https://doi.org/10.5755/j01.itc.49.1.23275
  • Falanga, D., Kleber, K., Mintchev, S., Floreano, D., & Scaramuzza, D. (2019). The Foldable Drone: A Morphing Quadrotor That Can Squeeze and Fly. IEEE Robotics and Automation Letters, 4(2), 209–216. https://doi.org/10.1109/LRA.2018.2885575
There are 3 citations in total.

Details

Primary Language English
Subjects Computer System Software
Journal Section Articles
Authors

Tugrul Oktay

Firat Sal

Oguz Kose

Abdullah Kocamer

Early Pub Date October 5, 2023
Publication Date September 30, 2023
Published in Issue Year 2023Volume: 23

Cite

APA Oktay, T., Sal, F., Kose, O., Kocamer, A. (2023). Stochastic Longitudinal Autopilot Tuning for Best Autonomous Flight Performance of a Morphing VTOL Drone. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 23, 413-419. https://doi.org/10.55549/epstem.1371783