AI Summary & Key Takeaways
AI InsightFinally, 10% improvement on autonomous performance index is achieved, and autopilot successfully tracks a reference trajectory with pitching angle of 30 degrees.
📌 3 Key Takeaways
Abstract
In this article, preliminary and conceptual design, dynamic modeling and flight dynamics modes of an unmanned aerial vehicle which have both helicopter flight mode and fixed-wing aircraft flight mode are investigated. The air vehicle (ZANKA-IV) which is planning to be produced in Erciyes University Faculty of Aeronautics and Astronautics Drone Laboratory captures both passive and active morphing properties. Furthermore, this hybrid unmanned aerial vehicle (HUAV) will be controlled by proportional-integral-derivative (PID) controller based autopilot system. In this article, sizes of morphing apparatuses and autonomous system are determined simultaneously in order to maximize autonomous flight performance for the first time. Also, a stochastic optimization method is applied for this simultaneous design. As a result of that, the optimum solution for design parameters is obtained very fast and accurately. Thus, as a result of this approach, autonomous control of HUAV becomes noticeably efficient. Finally, 10% improvement on autonomous performance index is achieved, and autopilot successfully tracks a reference trajectory with pitching angle of 30 degrees.