TY - JOUR
T1 - The Continuous Thrust Long-Orbit Satellite Pursuit-Evasion Game Control Using Feedback Genetic Shooting Method
AU - Yang, Shuai
AU - Tan, Minghu
AU - Zhang, Ke
AU - Xiong, Tianhao
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to The Korean Society for Aeronautical & Space Sciences 2024.
PY - 2024/10
Y1 - 2024/10
N2 - Considering the continuous thrust condition of satellites, the long-orbit satellite pursuit-evasion game emerges as a highly intricate challenge. To address this issue, this study initially adopts the Cartesian coordinate system, combined with feedback linearization techniques, to precisely construct a suboptimal control strategy for the game characterized by continuous thrust. With this strategy as a foundation, we further developed an innovative solution approach: utilizing the suboptimal control strategy as the initial value for the genetic algorithm, providing the algorithm with a reasonable starting point. To ensure the speed and efficiency of the solution, the shooting method is integrated for further optimization, allowing the algorithm to converge more swiftly when seeking the optimal solution. Then, a series of simulation experiments are undertaken to validate the effectiveness of this method. The results unequivocally demonstrate that, compared to the mixed global–local optimization strategy (MGLOS), traditional genetic (GA) algorithms, and differential evolution (DE) algorithms, our integrated approach exhibits significant advantages in both solution speed and accuracy.
AB - Considering the continuous thrust condition of satellites, the long-orbit satellite pursuit-evasion game emerges as a highly intricate challenge. To address this issue, this study initially adopts the Cartesian coordinate system, combined with feedback linearization techniques, to precisely construct a suboptimal control strategy for the game characterized by continuous thrust. With this strategy as a foundation, we further developed an innovative solution approach: utilizing the suboptimal control strategy as the initial value for the genetic algorithm, providing the algorithm with a reasonable starting point. To ensure the speed and efficiency of the solution, the shooting method is integrated for further optimization, allowing the algorithm to converge more swiftly when seeking the optimal solution. Then, a series of simulation experiments are undertaken to validate the effectiveness of this method. The results unequivocally demonstrate that, compared to the mixed global–local optimization strategy (MGLOS), traditional genetic (GA) algorithms, and differential evolution (DE) algorithms, our integrated approach exhibits significant advantages in both solution speed and accuracy.
KW - Differential game
KW - Genetic algorithm
KW - Long-orbit satellite pursuit-evasion game
KW - MGLOS
KW - Suboptimal control
UR - http://www.scopus.com/inward/record.url?scp=85192232992&partnerID=8YFLogxK
U2 - 10.1007/s42405-024-00740-6
DO - 10.1007/s42405-024-00740-6
M3 - 文章
AN - SCOPUS:85192232992
SN - 2093-274X
VL - 25
SP - 1507
EP - 1523
JO - International Journal of Aeronautical and Space Sciences
JF - International Journal of Aeronautical and Space Sciences
IS - 4
ER -