TY - GEN
T1 - Terminal Orbital Adaptive Dynamic Programming-based Control for Satellite Pursuit Evasion Game with Input Saturation
AU - Ma, Shuoheng
AU - Ma, Zhiqiang
AU - Zhang, Bo
AU - Huang, Panfeng
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - A continuous space pursuit-evasion game algorithm based on zero-sum game is proposed to solve the problem of the terminal pursuit-evasion control of spacecraft with input saturation. A novel single-network adaptive dynamic programming method is proposed to obtain the solution of zero-sum game. Firstly, it is assumed that the two satellites are close such that the nonlinear dynamics could be reduced to the CW equations. Considering the input saturation, a non-quadratic cost function is proposed to formulate a Hamilton-Jacobi-Isaacs equation. Then, only a critic neural network is employed to learn the optimal value function and further obtain the optimal controller, which enables the architecture of adaptive dynamic programming implementation to be simpler. An NN weight updating law is constructed, by which the restriction of initial admissible control is removed. Based on the Lyapunov theory, the convergence of critic NN weights and the stability of closed-loop system are guaranteed. Finally, numerical results verify the efficiency of the proposed method.
AB - A continuous space pursuit-evasion game algorithm based on zero-sum game is proposed to solve the problem of the terminal pursuit-evasion control of spacecraft with input saturation. A novel single-network adaptive dynamic programming method is proposed to obtain the solution of zero-sum game. Firstly, it is assumed that the two satellites are close such that the nonlinear dynamics could be reduced to the CW equations. Considering the input saturation, a non-quadratic cost function is proposed to formulate a Hamilton-Jacobi-Isaacs equation. Then, only a critic neural network is employed to learn the optimal value function and further obtain the optimal controller, which enables the architecture of adaptive dynamic programming implementation to be simpler. An NN weight updating law is constructed, by which the restriction of initial admissible control is removed. Based on the Lyapunov theory, the convergence of critic NN weights and the stability of closed-loop system are guaranteed. Finally, numerical results verify the efficiency of the proposed method.
KW - Adaptive dynamic programming
KW - orbital pursuit-evasion
KW - single neural network
KW - zero-sum game
UR - http://www.scopus.com/inward/record.url?scp=85173612820&partnerID=8YFLogxK
U2 - 10.1109/CFASTA57821.2023.10243254
DO - 10.1109/CFASTA57821.2023.10243254
M3 - 会议稿件
AN - SCOPUS:85173612820
T3 - Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023
SP - 1004
EP - 1009
BT - Proceedings of the 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd Conference on Fully Actuated System Theory and Applications, CFASTA 2023
Y2 - 14 July 2023 through 16 July 2023
ER -