RLV Reentry Trajectory Multi-Objective Optimization Design Based on NSGA2 Algorithm

Abstract

§Reentry trajectory Optimization is an important job in RLV preliminary design. A great many of optimization algorithms have been applied in solving this problem. But most of these applications just consider a single object such as minimum heat load or maximum maneuverable range. In practically, multi -objective reentry trajectory optimization is often necessary such as minimum heat load and maximum maneuverable range. These types of optimization problems have tr aditionally been solved by averaging each objective with a weighting factor, and then combine the objectives into a single scalar objective. Such reduction techniques eli minate the need for a more complex multi -objective algorithm, but introduce new parameters in the form of weighting factors. Except that，every run the algorithm can produce one optimal trajectory. NSGA -II algorithm is a good multi -objective genetic optimiz ation algorithm based on Pareto -optimal front with low computational requirements, elitist approach, parameter -less niche approach and simple constraint handling strategy. In this paper, NSGA -II algorithm is used to the RLV multi -objective reentry optimiza tion design with minimum heat load and maximum maneuverable range. The simulation result indicates that NSGA -II has good performance in reentry trajectory design and can produce all of the optimal results for different weighting factor.