Hypersonic reentry trajectory planning by using hybrid fractional-order particle swarm optimization and gravitational search algorithm  

作　　者：Khurram SHAHZAD SANA Weiduo HU 

机构地区：[1]School of Astronautics,Beihang University,Beijing 102206,China

出　　处：《Chinese Journal of Aeronautics》2021年第1期50-67,共18页中国航空学报（英文版）

摘　　要：This paper proposes a novel hybrid algorithm called Fractional-order Particle Swarm optimization Gravitational Search Algorithm(FPSOGSA)and applies it to the trajectory planning of the hypersonic lifting reentry flight vehicles.The proposed method is used to calculate the control profiles to achieve the two objectives,namely a smoother trajectory and enforcement of the path constraints with terminal accuracy.The smoothness of the trajectory is achieved by scheduling the bank angle with the aid of a modified scheme known as a Quasi-Equilibrium Glide(QEG)scheme.The aerodynamic load factor and the dynamic pressure path constraints are enforced by further planning of the bank angle with the help of a constraint enforcement scheme.The maximum heating rate path constraint is enforced through the angle of attack parameterization.The Common Aero Vehicle(CAV)flight vehicle is used for the simulation purpose to test and compare the proposed method with that of the standard Particle Swarm Optimization(PSO)method and the standard Gravitational Search Algorithm(GSA).The simulation results confirm the efficiency of the proposed FPSOGSA method over the standard PSO and the GSA methods by showing its better convergence and computation efficiency.

关 键 词：FRACTIONAL-ORDER Gravitational search algorithm Particle swarm optimization Reentry gliding vehicle Trajectory optimization 

分 类 号：V448[航空宇航科学与技术—飞行器设计] V41