Multi-constrained predictor-corrector reentry guidance for hypersonic vehicles

A numerical multi-constrained predictor-corrector guidance algorithm is proposed in this study, focusing on real-time longitudinal trajectory generation, constraint management, and lateral guidance improvement. First, a new compound bank corridor is designed to help convert the complicated trajectory planning problem into a root-finding problem, which is identified by a recursive least squares estimation algorithm and solved by a newly proposed period-crossing steepest descent method within a fraction of a second in Matlab. Second, three constraint enforcement operators are designed based on state prediction and feedback theory, and the long-standing constraint violation problem of predictor-corrector algorithms is addressed by on-board bank angle compensation. Additionally, a new predictive lateral guidance algorithm is proposed based on a cross-range proportional decrement strategy, and the resulting new bank reversal logic with only one user-defined parameter has better performance on reversal controllability and guidance robustness than the traditional algorithms. Finally, extensive numerical simulations are carried out for different mission scenarios with significant dispersions, and the new methodology is proved to be capable of autonomous and robust guidance flight for reentry vehicles.