Configuration enhancement for the flight endurance of a separate-lift-and-thrust hybrid unmanned aerial vehicle using Gaussian process optimization

• Main Author: Ng, Francis Gregory L.
• Format: text
• Language: English
• Published: Animo Repository 2019
• Subjects: Drone aircraft; Mechanical Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/6394; https://animorepository.dlsu.edu.ph/context/etd_masteral/article/13427/viewcontent/Thesis2.pdf
• Institution: De La Salle University

The modification of a fixed-wing drone to incorporate the features of a quadcopter (separate-lift-and-thrust) brings impactful practical gains without much technological investment. While this is a strong point in contrast to other vertical take-off and landing (VTOL) technologies, this simple approach incurs a tradeoff in performance. The added components are not tightly integrated to the form of the aircraft and may cause significant drag. Coupled with a direct increase in aircraft weight, the battery life is thereby affected. Expectedly, the shift in performance from the basic fixed-wing drone is dependent on the choice of components for augmenting the base. For this, there are a wide variety of options for selecting motors, propellers, and batteries, in addition to the mounting position of the components. An unguided choice may work for the hybrid drone, but it may likewise lead to a performance penalty more severe than otherwise necessary. To ensure a relatively good configuration, the impact of weight and drag on the battery life must be taken into account. But while the weight can be easily calculated, drag estimation requires a hefty cost. As such, a metamodeling-based optimization is needed to be more economical and to better utilize each of the evaluation results. Gaussian process optimization is employed in this case, having modifications to accommodate the categorical selection parameters along with the continuous positioning parameters.