采用利希滕贝格图的高超声速飞行器轨迹优化

A hybrid algorithm is proposed to solve the re-entry trajectory optimization problem of hypersonic flight vehicle under complex constraints to solve the shortcomings of existing trajectory optimization methods，such as strong dependence on initial values and easy to fall into local optimality. The hypersonic re-entry trajectory optimization is modeled as a nonlinear programming problem，and a two-layer optimization structure is designed to solve it. In the initial stage，an adaptive piecewise Lichtenberg algorithm（APLA）based on the Lichtenberg figure is proposed to obtain a good initial solution for Gauss pseudospectral method（GPM）. The efficiency of the initial trigger point of APLA is improved by introducing Latin hypercube sampling. The convergence speed and accuracy of the algorithm are improved and the situation that the algorithm is easy to fall into local optimization is improved by introducing global to local search piecewise strategy. GPM has better convergence speed and higher accuracy near the optimal solution，so in the final stage，it's used to speed up the search process and obtain the exact global optimal solution. In conclusion，a hybrid re-entry trajectory optimization algorithm（APLA_GPM）is proposed to solve the hypersonic re-entry trajectory optimization problem faster and more accurately. Simulation results show that the proposed algorithm has a faster convergence speed，higher accuracy，and stronger robustness for hypersonic vehicle re-entry trajectory optimization.