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

Creative Commons License

OKTAY T., KÖSE O., Sal F., Kocamer A.

International Conference on Research in Engineering, Technology and Science, ICRETS 2023, Budapest, Hungary, 6 - 09 July 2023, vol.23, pp.413-419 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 23
  • Doi Number: 10.55549/epstem.1371783
  • City: Budapest
  • Country: Hungary
  • Page Numbers: pp.413-419
  • Keywords: Autonomous performance, Morphing, Stochastic optimization, VTOL drone
  • Erzincan Binali Yildirim University Affiliated: Yes


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.