The Success of the Hybrid Genetic and Particle Swarm Algorithm for a Return Spacecraft from the Atmosphere with an Optimal Trajectory Design Approach to Reduce Aerodynamic Heat Transfer

This study aims to investigate the spacecraft returning from the atmosphere. Due to high speed, prolonged flight duration, and numerical sensitivity, returning from the atmosphere is regarded as one of the more challenging tasks in route design. Our suborbital system is subjected to a substantial thermal load as a result of its return at high speed and the presence of uncertainty. In addition, the current study aims to lessen the thermal load in the system to meet the needs of the initial and final conditions through multi-subject optimization, comparison of the two fields of aerodynamics and flight dynamics, assistance from optimal control theory, and consideration of uncertainties The heat load in the sub-orbital system could be reduced by around 9.6% using these algorithms and optimum control theory. Artificial bee colonies, genetic algorithms, and the combined genetic algorithms and particle swarm algorithms were utilized as exploratory optimization techniques. The objective of the flight mechanics system is also to create the best trajectory while taking into account uncertainty and minimizing thermal load. The conduction law based on heat reduction is described in the search for the ideal trajectory. We reduced the heat rate during the first part of the spacecraft's return journey from the atmosphere by concentrating on the angle of attack. By more accurately specifying the angle of attack and the angle of the bank in the second stage of the split guidance legislation, the ultimate return requirements could be achieved significantly .