Parameter Optimization Method for Predictor–Corrector Guidance With Impact Angle Constraint

With the applications of predictor–corrector guidance technology on hypersonic vehicles, the stability and robustness of the predictor–corrector algorithm have become issues of concern. Currently, the key parameters of predictor–corrector guidance law often rely on the designer’s experience and trial-and-error selection. It requires a significant amount of time for comprehensive testing to verify its reliability, lacking a theoretical basis for stability and robustness analysis. In this paper, a nonlinear model is proposed to describe the prediction process. Based on this model, the stability and stability margin of the predictor–corrector guidance system can be calculated using the Nyquist stability theory. The upper bounds of the key parameters in the algorithm of corrector can be deduced according to the requirement for the system’s stability margin. Additionally, an uncertainty factor is proposed to describe the model uncertainty in the predictor–corrector guidance algorithm. Based on the uncertainty factor, the impact of uncertainty and external disturbances on prediction accuracy is derived, and the propagation of prediction error to the miss distance is analyzed using the adjoint method. The lower bounds of key parameters can be deduced by the requirement for the guidance precision index. Finally, this paper proposes a parameter optimization algorithm that can satisfy the requirements of stability and guidance precision. A Monte Carlo simulation has verified its effectiveness and reliability.