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Article

Optimal Midcourse Guidance with Terminal Relaxation and Range Convex Optimization

Air Defense and Antimissile School, Air Force Engineering University, Xi’an 710038, China
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Author to whom correspondence should be addressed.
Aerospace 2025, 12(7), 618; https://doi.org/10.3390/aerospace12070618
Submission received: 29 April 2025 / Revised: 7 July 2025 / Accepted: 8 July 2025 / Published: 9 July 2025
(This article belongs to the Special Issue Dynamics, Guidance and Control of Aerospace Vehicles)

Abstract

In midcourse guidance, strong constraints and dual-channel control coupling pose major challenges for trajectory optimization. To address this, this paper proposes an optimal guidance method based on terminal relaxation and range convex programming. The study first derived a range-domain dynamics model with the angle of attack and bank angle as dual control inputs, augmented with path constraints including heat flux limitations, to formulate the midcourse guidance optimization problem. A terminal relaxation strategy was then proposed to mitigate numerical infeasibility induced by rigid terminal constraints, thereby guaranteeing the solvability of successive subproblems. Through the integration of affine variable transformations and successive linearization techniques, the original nonconvex problem was systematically converted into a second-order cone programming (SOCP) formulation, with theoretical equivalence between the relaxed and original problems established under well-justified assumptions. Furthermore, a heuristic initial trajectory generation scheme was devised, and the solution was obtained via a sequential convex programming (SCP) algorithm. Numerical simulation results demonstrated that the proposed method effectively satisfies strict path constraints, successfully generates feasible midcourse guidance trajectories, and exhibits strong computational efficiency and robustness. Additionally, a systematic comparison was conducted to evaluate the impact of different interpolation methods and discretization point quantities on algorithm performance.
Keywords: convex optimization; midcourse guidance; dual-channel control; sequential convex programming; second-order cone programming convex optimization; midcourse guidance; dual-channel control; sequential convex programming; second-order cone programming

Share and Cite

MDPI and ACS Style

Li, J.; Zhang, J.; Ye, J.; Shao, L.; Bu, X. Optimal Midcourse Guidance with Terminal Relaxation and Range Convex Optimization. Aerospace 2025, 12, 618. https://doi.org/10.3390/aerospace12070618

AMA Style

Li J, Zhang J, Ye J, Shao L, Bu X. Optimal Midcourse Guidance with Terminal Relaxation and Range Convex Optimization. Aerospace. 2025; 12(7):618. https://doi.org/10.3390/aerospace12070618

Chicago/Turabian Style

Li, Jiong, Jinlin Zhang, Jikun Ye, Lei Shao, and Xiangwei Bu. 2025. "Optimal Midcourse Guidance with Terminal Relaxation and Range Convex Optimization" Aerospace 12, no. 7: 618. https://doi.org/10.3390/aerospace12070618

APA Style

Li, J., Zhang, J., Ye, J., Shao, L., & Bu, X. (2025). Optimal Midcourse Guidance with Terminal Relaxation and Range Convex Optimization. Aerospace, 12(7), 618. https://doi.org/10.3390/aerospace12070618

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