TY - GEN
T1 - A Nonlinear Pursuit-Evasion Game Trajectory Planning Method for Spacecrafts with Low Sensitivity on the Initial Value
AU - Yang, Zhiyuan
AU - Wang, Honglun
AU - Zhang, Menghua
AU - Wu, Jianfa
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Aiming at the nonlinear pursuit-evasion game problems of the spacecrafts, an improved Radau pseudo-spectral method whose initial values are pre-optimized by a hybrid optimization algorithm is proposed. This method transforms the nonlinear pursuit-evasion game problem considering J2 term perturbations, a bilateral optimal problem, into a unilateral optimal control problem based on the semi-direct method. Subsequently, hp-Radau pseudo-spectral method is used to further transform the unilateral optimal control problem into a nonlinear programming problem. Then, a hybrid optimization algorithm composed of the designed nonlinear adaptive particle swarm optimization (NAPSO) algorithm and the collocation method is to pre-optimize the initial guess value of the nonlinear programming problem, which is solved by the nonlinear programming solver. After that, the optimal control strategy and game trajectory of the spacecrafts can be obtained. Finally, the simulation results show that the proposed method can maintain high solution accuracy and efficiency with limited computational cost compared to the combined shooting and collocation method (CSCM), while reducing the initial value sensitivity of the method.
AB - Aiming at the nonlinear pursuit-evasion game problems of the spacecrafts, an improved Radau pseudo-spectral method whose initial values are pre-optimized by a hybrid optimization algorithm is proposed. This method transforms the nonlinear pursuit-evasion game problem considering J2 term perturbations, a bilateral optimal problem, into a unilateral optimal control problem based on the semi-direct method. Subsequently, hp-Radau pseudo-spectral method is used to further transform the unilateral optimal control problem into a nonlinear programming problem. Then, a hybrid optimization algorithm composed of the designed nonlinear adaptive particle swarm optimization (NAPSO) algorithm and the collocation method is to pre-optimize the initial guess value of the nonlinear programming problem, which is solved by the nonlinear programming solver. After that, the optimal control strategy and game trajectory of the spacecrafts can be obtained. Finally, the simulation results show that the proposed method can maintain high solution accuracy and efficiency with limited computational cost compared to the combined shooting and collocation method (CSCM), while reducing the initial value sensitivity of the method.
UR - https://www.scopus.com/pages/publications/105016143417
U2 - 10.1109/ICCA65672.2025.11129833
DO - 10.1109/ICCA65672.2025.11129833
M3 - 会议稿件
AN - SCOPUS:105016143417
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 698
EP - 703
BT - 2025 IEEE 19th International Conference on Control and Automation, ICCA 2025
PB - IEEE Computer Society
T2 - 19th IEEE International Conference on Control and Automation, ICCA 2025
Y2 - 30 June 2025 through 3 July 2025
ER -