A Dimension-reduction method for the finite-horizon spacecraft pursuit-evasion game

Qisuai Wang, Pei Li, Ting Lei, Xiaofeng Liu, G. Cai
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Abstract

The finite-horizon two-person zero-sum differential game is a significant technology to solve the finite-horizon spacecraft pursuit-evasion game (SPE game). Considering that the saddle point solution of the differential game usually results in solving a high-dimensional (24 dimensional in this paper) two-point boundary value problem (TPBVP) that is challengeable, a dimension-reduction method is proposed in this paper to simplify the solution of the 24-dimensional TPBVP related to the finite-horizon SPE game and to improve the efficiency of the saddle point solution. In this method, firstly, the 24-dimensional TPBVP can be simplified to a 12-dimensional TPBVP by using the linearization of the spacecraft dynamics; then the adjoint variables associated with the relative state variables between the pursuer and evader can be expressed in the form of state transition; after that, based on the necessary conditions for the saddle point solution and the adjoint variables in the form of state transition, the 12-dimensional TPBVP can be transformed into the solving of 6-dimensional nonlinear equations; finally, a hybrid numerical algorithm is developed to solve the nonlinear equations so as to obtain the saddle point solution. The simulation results show that the proposed method can effectively obtain the saddle point solution and is robust to the interception time, the orbital altitude and the initial relative states between the pursuer and evader.
有限视界航天器追逃博弈的降维方法
有限视界二人零和微分对策是求解有限视界航天器追逃对策的重要技术。考虑到微分对策的鞍点解通常求解高维(本文为24维)两点边值问题(TPBVP),该问题具有挑战性,本文提出了一种降维方法,简化了有限视界SPE对策相关的24维两点边值问题的求解,提高了鞍点解的效率。该方法首先利用航天器动力学的线性化,将24维TPBVP简化为12维TPBVP;然后,追赶者和逃避者之间的相对状态变量的伴随变量可以用状态转换的形式表示;然后,根据鞍点解的必要条件和状态转换形式的伴随变量,将12维TPBVP转化为6维非线性方程的求解;最后,提出了一种求解非线性方程组的混合数值算法,从而得到鞍点解。仿真结果表明,该方法能有效地获得鞍点解,且对拦截时间、轨道高度和追踪器与规避器之间的初始相对状态具有鲁棒性。
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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