Ascent Phase Trajectory Optimization for Hypersonic Vehicle Using hp-Adaptive Pseudo-spectral Method

Abstract

An improved hp adaptive pseudo-spectral method ia scaling parameters designed for the hypersonic vehicle trajectory optimization problem. In this paper, we take hypersonic vehicle as the research object, consider its ascent phase with various constraints, and establish a multi-constrained climbing segment trajectory optimization model with the shortest ascent time as the objective function. Because the nonlinear programming problem (NLP) obtained by applying the hp adaptive pseudo-spectral method to discretize the trajectory optimization model has high dimensionality, which makes the trajectory optimization problem difficult to solve, we propose an improved hp adaptive pseudo-spectral method. The algorithm uses the improved wild horse optimizer (IWHO) algorithm to adjust the distribution of interpolation nodes and the order of interpolation polynomials in the trajectory optimization subinterval, which avoids unnecessary mesh refinement and reduces the dimensionality of the discretized obtained NLP with a given precision, and improves the efficiency of the trajectory optimization solution. Simulation results show that the trajectories solved by the designed hybrid optimization algorithm satisfy all process constraints and terminal constraints.