Real-Time Lateral Predictor-Corrector Entry Guidance With Terminal Heading Angle Constraint

Predictor-corrector guidance (PCG) methods for entry flight are valued for their flexibility and adaptability. This study focuses on the lateral control of PCG with an added terminal heading angle constraint. Specifically, we propose a real-time lateral PCG algorithm that first achieves the online c...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems Vol. 61; no. 2; pp. 2106 - 2119
Main Authors: Shi, Peng, Xu, Jingjing, Cheng, Lin, Dong, Changhong, Huang, Xu
Format: Journal Article
Language:English
Published: New York IEEE 01.04.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Aerodynamics
Aerospace and electronic systems
Algorithms
Artificial neural networks
Constraints
Controllability
Cooperative guidance
entry guidance
Flight
heading coordination
Heuristic algorithms
Lateral control
lateral guidance logic
Prediction algorithms
Predictor-corrector methods
predictor–corrector guidance (PCG)
Real time
Real-time systems
Sliding mode control
terminal heading angle constraint
Tracking errors
Trajectories
Trajectory
Vehicle dynamics
ISSN:0018-9251, 1557-9603
Online Access:Get full text
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Summary:Predictor-corrector guidance (PCG) methods for entry flight are valued for their flexibility and adaptability. This study focuses on the lateral control of PCG with an added terminal heading angle constraint. Specifically, we propose a real-time lateral PCG algorithm that first achieves the online controllability of terminal heading angle approaching the target site. Our contributions include: 1) deriving an analytical expression for lateral trajectory prediction using a reasonably simplified entry flight model; 2) introducing a wide-range heading adjustment strategy based on the derived expression. This strategy enables online determination of the bank angle direction and reversal time, allowing for adjustment of the lateral trajectory to approach and follow the desired heading baseline; and 3) developing a discrete sliding mode guidance method to correct lateral tracking errors for subsequent lateral control, balancing reversal frequency and tracking accuracy. Combining this lateral guidance with our previously proposed deep neural networks-based longitudinal guidance method, we establish a real-time 3-D entry guidance algorithm. Simulations and Monte Carlo experiments confirm the algorithm's real-time performance, robustness, and terminal heading angle controllability.
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ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2024.3466125