Ascent Trajectory Optimization for Air-Breathing Hypersonic Vehicles Based on IGS-MPSP

Lei Liu, Qianwei He, Bo Wang, Wenzhe Fu, Zhongtao Cheng, Wang Yongji
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引用次数: 1

Abstract

This paper proposes an improved Generalized Quasi-Spectral Model Predictive Static Programming (GS-MPSP) algorithm for the ascent trajectory optimization for hypersonic vehicles in a complex flight environment. The proposed method guarantees the satisfaction of constraints related to the state and control vector while retaining its high computational efficiency. The spectral representation technique is used to describe the control variables, which reduces the number of decision variables and makes the control input smooth enough. Through Taylor expansion, the constraints are transformed into an inequality containing only decision variables, such that it can be added into GS-MPSP framework. By Gauss quadrature collocation method, only a few collocation points are needed to solve the sensitivity matrix, which greatly accelerates the calculation. Subsequently, the analytical expression is obtained by combining the static optimization with the penalty function method. Finally, the simulation results demonstrate that the proposed improved GS-MPSP algorithm can achieve both high computational efficiency and high terminal precision under the constraints.
基于IGS-MPSP的吸气式高超声速飞行器上升轨迹优化
针对高超声速飞行器复杂飞行环境下的上升轨迹优化问题,提出了一种改进的广义准谱模型预测静态规划算法。该方法在保证状态约束和控制向量约束满足的同时,保持了较高的计算效率。采用谱表示技术对控制变量进行描述,减少了决策变量的数量,使控制输入足够平滑。通过Taylor展开式,将约束转化为一个只包含决策变量的不等式,从而可以将其加入到GS-MPSP框架中。采用高斯正交配点法,求解灵敏度矩阵只需几个配点法,大大加快了计算速度。随后,将静态优化与罚函数法相结合,得到了解析表达式。仿真结果表明,在约束条件下,改进的GS-MPSP算法能够实现较高的计算效率和终端精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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