TY - GEN
T1 - Koopman Predictor-based Sliding Mode Control for Strapdown Interceptor under Divert and Attitude Control System
AU - Peng, Qian
AU - Chen, Gang
AU - Guo, Jianguo
AU - Guo, Zongyi
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This paper proposes a Koopman predictor-based sliding mode control (KPSMC) method for the strapdown interceptor under the divert and attitude control system (DACS). The kinematic and dynamic equations of the strapdown interceptor are constructed firstly, including the strapdown interceptor-target relative motion equations, strongly coupled dynamic model of DACS and the mapping state of the body line-of-sight (BLOS) angle. Then, considering the mapping state of the constrained field-of-view (FOV), the Koopman predictor is established for the guidance and control systems with strong coupling and nonlinearity. Finally, the controller of the strapdown interceptor is designed by combining the Koopman predictor and the sliding mode control (SMC) theory, which simplifies the design difficulty of DACS-based controller and enhances the control capability of the BLOS angle while accomplishing the required control accuracy. The effectiveness of the proposed predictor and control law is checked by the comparison simulations, and the robustness of the proposed law is demonstrated by the Monte Carlo tests.
AB - This paper proposes a Koopman predictor-based sliding mode control (KPSMC) method for the strapdown interceptor under the divert and attitude control system (DACS). The kinematic and dynamic equations of the strapdown interceptor are constructed firstly, including the strapdown interceptor-target relative motion equations, strongly coupled dynamic model of DACS and the mapping state of the body line-of-sight (BLOS) angle. Then, considering the mapping state of the constrained field-of-view (FOV), the Koopman predictor is established for the guidance and control systems with strong coupling and nonlinearity. Finally, the controller of the strapdown interceptor is designed by combining the Koopman predictor and the sliding mode control (SMC) theory, which simplifies the design difficulty of DACS-based controller and enhances the control capability of the BLOS angle while accomplishing the required control accuracy. The effectiveness of the proposed predictor and control law is checked by the comparison simulations, and the robustness of the proposed law is demonstrated by the Monte Carlo tests.
KW - Koopman predictor
KW - Strapdown interceptor
KW - divert and attitude control system
KW - sliding mode control
UR - https://www.scopus.com/pages/publications/105012152162
U2 - 10.1109/ICAISISAS64483.2025.11051865
DO - 10.1109/ICAISISAS64483.2025.11051865
M3 - 会议稿件
AN - SCOPUS:105012152162
T3 - 2025 Joint International Conference on Automation-Intelligence-Safety, ICAIS 2025 and International Symposium on Autonomous Systems, ISAS 2025
BT - 2025 Joint International Conference on Automation-Intelligence-Safety, ICAIS 2025 and International Symposium on Autonomous Systems, ISAS 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 Joint International Conference on Automation-Intelligence-Safety, ICAIS 2025 and International Symposium on Autonomous Systems, ISAS 2025
Y2 - 23 May 2025 through 25 May 2025
ER -