Fast Trajectory Optimization for Gliding Reentry Vehicle Based on Improved Sparrow Search Algorithm

Abstract

Abstract In order to solve the problem of low convergence accuracy and easy to fall into local optimization when solving the reentry vehicle trajectory optimization problem for existing algorithms, an improved sparrow search algorithm (OTRSSA) is proposed. Firstly, the basic sparrow search algorithm is improved by the methods of opposition-based learning, adaptive T-distribution and random walk to improve the optimization accuracy and stability, and increase the global search ability, and the performance verification is carried out in 12 benchmark functions; secondly, the 3-DOF motion model of reentry trajectory optimization problem is established and transformed into multi-dimensional function optimization problem; finally, OTRSSA is applied to solve the trajectory optimization problem. The simulation results show that the optimization performance and convergence speed of OTRSSA are better, and a reentry trajectory with the farthest range and satisfying constraints can be obtained quickly.