Koopman Operator-Based Integrated Guidance and Control for Strap-Down High-Speed Missiles
Min Zhou, Mingfei Lu, Guanjie Hu, Zongyi Guo, Jianguo Guo
Abstract
This work focuses on addressing the challenges of integrated guidance and control (IGC) for strap-down high-speed missiles with nonlinearities and field-of-view constraints. To achieve this, a data-driven prediction model using the Koopman operator is developed, which exhibits high accuracy in capturing the significant nonlinearities of the investigated high-speed missiles. Furthermore, the field-of-view restrictions imposed by the strap-down seeker are addressed by introducing a Lyapunov-based model predictive control (LMPC) scheme based on the linear Koopman prediction model. To enhance the robustness of the system, a disturbance observer is integrated into the Koopman-operator-based LMPC (KLMPC), enabling the estimation and compensation of disturbances. A KLMPC-based IGC (KLMPC-IGC) design framework is then developed to solve the constrained IGC problem, ensuring the stability and robustness of the closed-loop system. Numerical simulation results validate the higher prediction accuracy of the proposed linear prediction model compared with traditional local linearization prediction, as well as demonstrate the effectiveness of the presented approach.