@article{LIU2025, 
author = {Yuchen LIU and Chaoyong LI and Jun JIANG and Yonghe ZHANG},
title = {A model predictive Stackelberg solution to orbital pursuit-evasion game},
year = {2025},
journal = {Chinese Journal of Aeronautics},
volume = {38},
number = {2},
keywords = {Model predictive control, Pursuit-evasion problem, Leader-follower game, Stackelberg game, Orbital game},
url = {https://www.sciopen.com/article/10.1016/j.cja.2024.08.029},
doi = {10.1016/j.cja.2024.08.029},
abstract = {In this paper, we investigate analytical numerical iterative strategies for the pursuit-evasion game involving spacecraft with leader–follower information. In the proposed problem, the interplay between two spacecraft gives rise to a dynamic and real-time game, complicated further by the presence of  perturbation. The primary challenge lies in crafting control strategies that are both efficient and applicable to real-time game problems within a nonlinear system. To overcome this challenge, we introduce the model prediction and iterative correction technique proposed in model predictive static programming, enabling the generation of strategies in analytical iterative form for nonlinear systems. Subsequently, we proceed by integrating this model predictive framework into a simplified Stackelberg equilibrium formulation, tailored to address the practical complexities of leader–follower pursuit-evasion scenarios. Simulation results validate the effectiveness and exceptional efficiency of the proposed solution within a receding horizon framework.}
}