Abstract
Flexible skin and continuous deformable control surface are the basic of adaptive wing technology for future aircraft. This paper presents a continuous morphing trailing-edge and its control allocation method for the flying wing Unmanned Aerial Vehicle (UAV). Firstly, we apply the Kriging method to establish the aerodynamic model of the morphing trailing-edge, with the initial sample points generated by the non-uniform optimal Latin Hypercube Sampling (LHS). Then, based on the Kriging model, the multi-objective control allocation problem is converted into a standard optimization form. To solve such problem, we design a Comprehensive Multi-Objective Particle Swarm Optimization (C-MOPSO) algorithm and an improved Hierarchical MOPSO (H-MOPSO) algorithm, in which multiple optimization objectives are prioritized and hierarchically optimized using the PSO algorithm. As for performance analysis, an attitude angle tracking flight control system is established to validate the effectiveness of our proposed control allocation methods. Simulation results show that both the C-MOPSO and H-MOPSO methods have similar performance in attitude angle tracking, while H-MOPSO achieves better multi-objective allocation performance.
Highlights
Compared with conventional Unmanned Aerial Vehicle (UAV), flying wing UAVs adopt the blended-wing-body configuration and eliminate the empennage, they have more advantages in aerodynamic, structural and stealth performance, such as an extremely low radar cross-section (RCS) and a significant reduction in fuel consumption and aerodynamic noise [1], [2]
Considering the above rationale, this paper aims to provide solutions to the above design, and the main contributions of this paper can be summarized as follows: (1) A continuously morphing trailing-edge control surface is designed for a flying wing UAV
For each morphing trailing-edge configuration determined by the Design of Experiment (DoE), the corresponding 3D shape model of the flying wing UAV is established in XFLR5, while the 3D panel method is used to quickly obtain the aerodynamic parameters
Summary
Compared with conventional UAVs, flying wing UAVs adopt the blended-wing-body configuration and eliminate the empennage, they have more advantages in aerodynamic, structural and stealth performance, such as an extremely low radar cross-section (RCS) and a significant reduction in fuel consumption and aerodynamic noise [1], [2]. (2) The Kriging algorithm is innovatively adopted to establish the aerodynamic model of morphing trailing-edge and to solve the control allocation problem. (3) We design two effective and heuristic algorithms for the control allocation problem based on Kriging aerodynamic modeling, namely, C-MOPSO and H-MOPSO Both algorithms are PSO-based methods to solve the multi-objective optimization, in which C-MOPSO has advantages in algorithm efficiency and realizability, but the result may not be optimal. According to the selected initial sample points, we choose the three-dimensional (3D) panel method to evaluate the aerodynamic characteristics of the morphing trailing-edge flying wing UAV under various actuator deflections. For each morphing trailing-edge configuration determined by the DoE, the corresponding 3D shape model of the flying wing UAV is established in XFLR5, while the 3D panel method is used to quickly obtain the aerodynamic parameters
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
