A path planning model of a tiltrotor for approaching an aircraft carrier during landing. (December 2021)

• Record Type: Journal Article
• Authors: Wu, Yu; Li, Haixu; Su, Xichao
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 235:Number 16(2021)
• Page Start: 2392
• Page End: 2406
• Publication Date: 2021-12
• Subjects: Path planning -- tiltrotor -- aircraft carrier -- multiple flight modes -- pigeon inspired optimization; Aeronautics -- Periodicals; Astronautics -- Periodicals; Airplanes -- Design and construction -- Periodicals; Aerospace industries -- Periodicals; 629.1
• DOI: 10.1177/0954410021996491
• Languages: English
• ISSNs: 0954-4100

Abstract

A path planning model concerning a tiltrotor approaching an aircraft carrier is established in this study. In the model, the characteristic of the tiltrotor, the landing task, and the environment of the carrier are taken into account. First, the motion equations and the maneuverability of the tiltrotor in each flight mode are presented, and the constraints of control variables and flight envelope are given. The returning flight of the tiltrotor is divided into three phases corresponding to the three flight modes of the tiltrotor, and the constraints in each phase and the goal are set. Considering the flight safety of the tiltrotor, the environment of the carrier is described as flyable space and no-fly zones, and the no-fly zones are set taking the influences of turbulence and wind field induced by the moving aircraft carrier into account. The path planning issue is formulated into an optimization problem under the constraints of control variables and state variables. According to the characteristic of the established model, a pigeon inspired optimization (PIO)-based path planning algorithm is developed integrating the "step-by-step" and "one effort" path search strategies. Simulation results demonstrate that the tiltrotor can reach the target point with a reasonable landing path. Comparison among different algorithms is also conducted to verify that the PIO algorithm is capable of solving this online path planning problem.