Conference Paper
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Year 2023, Volume: 23, 50 - 58, 30.09.2023
https://doi.org/10.55549/epstem.1357605

Abstract

References

  • Abdelhay, S., & Zakriti, A. (2019). Modeling of a quadcopter trajectory tracking system using PID controller. Procedia Manufacturing, 32, 564–571.
  • 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.
  • Austin, R. (2011). Unmanned aircraft systems: UAVS design, development and deployment, 54. John Wiley & Sons.
  • Desbiez, A., Expert, F., Boyron, M., Diperi, J., Viollet, S., Ruffier, F., Desbiez, A., Expert, F., Boyron, M., Diperi, J., Viollet, S., Desbiez, A., Expert, F., Boyron, M., Diperi, J., Viollet, S., & Ruffier, F. (2017). X-Morf : a crash-separable quadrotor that morfs its X-geometry in flight To cite this version : HAL Id : hal-01644528.

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

Year 2023, Volume: 23, 50 - 58, 30.09.2023
https://doi.org/10.55549/epstem.1357605

Abstract

In this conference paper autonomous flight performance maximization of a morphing decacopter is considered by using stochastic optimization approach. For flight controller a PID based hierarchical control system is chosen. In this paper PID controller which is used for pitch angle is considered. In this application only longitudinal flight and longitudinal autopilot is considered where the pitch motion is in primary interest and the used controller is the pitch control. For optimization technique simultaneous perturbation stochastic approximation (i.e., SPSA) is selected. It is fast and safe in stochastic optimization problems when it is not possible to evaluate gradient analytically. At the end a cost function consisting terms that settling time, rise time and overshoot is minimized. A detailed graphical analysis is done in order to better present effect of morphing on longitudinal flight of decacopter flight. Moreover, the cost function consist of rise time, settling time, and overshoot during trajectory tracking.

References

  • Abdelhay, S., & Zakriti, A. (2019). Modeling of a quadcopter trajectory tracking system using PID controller. Procedia Manufacturing, 32, 564–571.
  • 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.
  • Austin, R. (2011). Unmanned aircraft systems: UAVS design, development and deployment, 54. John Wiley & Sons.
  • Desbiez, A., Expert, F., Boyron, M., Diperi, J., Viollet, S., Ruffier, F., Desbiez, A., Expert, F., Boyron, M., Diperi, J., Viollet, S., Desbiez, A., Expert, F., Boyron, M., Diperi, J., Viollet, S., & Ruffier, F. (2017). X-Morf : a crash-separable quadrotor that morfs its X-geometry in flight To cite this version : HAL Id : hal-01644528.
There are 4 citations in total.

Details

Primary Language English
Subjects Electronic Device and System Performance Evaluation, Testing and Simulation
Journal Section Articles
Authors

Tugrul Oktay

Firat Sal

Oguz Kose

Enes Ozen

Early Pub Date September 9, 2023
Publication Date September 30, 2023
Published in Issue Year 2023Volume: 23

Cite

APA Oktay, T., Sal, F., Kose, O., Ozen, E. (2023). Stochastic Longitudinal Autopilot Tuning for Best Autonomous Flight Performance of a Morphing Decacopter. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 23, 50-58. https://doi.org/10.55549/epstem.1357605