Reentry Trajectory Optimization for a Hypersonic Vehicle Based on an Improved Adaptive Fireworks Algorithm

Xing Wei,Yongji Wang,Ye Yang,Lei Liu

doi:10.1155/2018/8793908

Abstract

Generation of optimal reentry trajectory for a hypersonic vehicle (HV) satisfying both boundary conditions and path constraints is a challenging task. As a relatively new swarm intelligent algorithm, an adaptive fireworks algorithm (AFWA) has exhibited promising performance on some optimization problems. However, with respect to the optimal reentry trajectory generation under constraints, the AFWA may fall into local optimum, since the individuals including fireworks and sparks are not well informed by the whole swarm. In this paper, we propose an improved AFWA to generate the optimal reentry trajectory under constraints. First, via the Chebyshev polynomial interpolation, the trajectory optimization problem with infinite dimensions is transformed to a nonlinear programming problem (NLP) with finite dimension, and the scope of angle of attack (AOA) is obtained by path constraints to reduce the difficulty of the optimization. To solve the problem, an improved AFWA with a new mutation strategy is developed, where the fireworks can learn from more individuals by the new mutation operator. This strategy significantly enhances the interactions between the fireworks and sparks and thus increases the diversity of population and improves the global search capability. Besides, a constraint-handling technique based on an adaptive penalty function and distance measure is developed to deal with multiple constraints. The numerical simulations of two reentry scenarios for HV demonstrate the validity and effectiveness of the proposed improved AFWA optimization method, when compared with other optimization methods.

Highlights

In recent decades, global strike and space transportation have spurred more and more interests in hypersonic vehicles (HVs) [1] for both military and civilian applications
We focus on the improvement of the adaptive fireworks algorithm (AFWA) and its application to the reentry trajectory optimization problems
In order to verify the effectiveness of the proposed algorithm, the improved version of the AFWA (I-AFWA) is tested in comparison with the standard AFWA (S-AFWA), differential evolution (DE), particle swarm optimization (PSO), genetic algorithm (GA), and fireworks algorithm (FWA)

Summary

Introduction

Global strike and space transportation have spurred more and more interests in hypersonic vehicles (HVs) [1] for both military and civilian applications. The development of advanced guidance and control technologies for HV is promoted to meet the need for an effective and reliable access to the space. The unpowered HV has the ability of reentering and gliding through the atmosphere. In order to steer an efficient and safety flight in the complex conditions, the reentry trajectory optimization problem of HV has been widely of concern. The aim of reentry trajectory optimization is to find an optimal solution under the reentry flight dynamics and physics, given the aerodynamics, structural strength, and the thermal protection system [2]. As the reentry dynamics is highly nonlinear, the reentry trajectory optimization is a nonconvex problem with multiple constraints, such as the control ability, heating rate, dynamic pressure, and aerodynamic load. It is difficult to solve these problems analytically, and numerical techniques are required to determine an approximation to the continuous solution

Methods

Results

Conclusion