Constrained reentry trajectory optimization based on improved particle swarm optimization algorithm

Tianyun Xu; Jun Zhou; Jianguo Guo; Qing Lu

doi:10.1117/12.2586769

12 March 2021 Constrained reentry trajectory optimization based on improved particle swarm optimization algorithm

Tianyun Xu, Jun Zhou, Jianguo Guo, Qing Lu

Proceedings Volume 11763, Seventh Symposium on Novel Photoelectronic Detection Technology and Applications; 117633V (2021) https://doi.org/10.1117/12.2586769
Event: Seventh Symposium on Novel Photoelectronic Detection Technology and Application 2020, 2020, Kunming, China

Abstract

This paper proposes an improved particle swarm optimization (PSO) using "step-phase" adjustment strategy for inertia weight to generate the minimum time reentry trajectory for hypersonic reentry vehicles based on the parameterized bank angle profile. According to engineering experience, the velocity-dependent bank angle profile is developed using the "two-flip strategy", thereby reducing the dimensionality of particles. The reentry constraints are processed by penalty function. Especially, the no-fly zone (NFZ) constraint is enforced by extreme method that setting penalty weight to be an extremely large positive number on the condition that the trajectory passes through the NFZ . Simulation results illustrate that the improved PSO algorithm based on the parameterized bank angle profile proves to be capable to generate a complete and optimal three degrees of freedom (3-DOF) reentry trajectory rapidly.

Citation Download Citation

Tianyun Xu, Jun Zhou, Jianguo Guo, and Qing Lu "Constrained reentry trajectory optimization based on improved particle swarm optimization algorithm", Proc. SPIE 11763, Seventh Symposium on Novel Photoelectronic Detection Technology and Applications, 117633V (12 March 2021); https://doi.org/10.1117/12.2586769

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