Reentry guidance method considering flight time based on convex optimization

Abstract

The invention relates to a reentry guidance method considering flight time based on convex optimization. The method comprises the following steps: (1) establishing an aircraft reentry section dynamicmodel; (2) defining a heeling angle change curve in a quadratic function cosine form and control parameters of the heeling angle change curve; (3) establishing a course angle error corridor, reversingthe symbol of the heeling angle, and determining the symbol of the heeling angle; (4) establishing a trajectory planning problem model considering a terminal height constraint, a terminal speed constraint, a flight time constraint and a terminal inclination angle constraint; (5) converting the trajectory planning problem model into a nonlinear equation set solving problem model; (6) introducing arelaxation variable and a penalty function, and converting a nonlinear equation set solving problem into a convex optimization problem model; and (7) quickly and accurately solving the convex optimization problem model in the step (6) by applying a convex optimization solving algorithm to obtain a heeling angle change curve in a quadratic function cosine form and control parameters thereof.

Description

technical field [0001] The invention relates to a re-entry guidance method considering flight time based on convex optimization, and belongs to the field of advanced guidance of re-entry aircraft. Background technique [0002] The commonly used re-entry guidance algorithms at this stage are divided into nominal guidance method and predictive-correction guidance method. The nominal guidance method means that after the corresponding reference trajectory is specified according to the flight mission requirements, a new reference trajectory will not be re-planned during the actual flight phase. The nominal guidance algorithm has the advantages of being simple and fast, but in the face of unknown events such as flight mission changes or airframe device failures, the task adaptability of the guidance algorithm is weak. The prediction-correction guidance algorithm needs to plan a new reference flight trajectory in real time according to the flight state and terminal landing point. ...

AI Technical Summary

Problems solved by technology

The nominal guidance algorithm has the advantages of being simple and fast, but in the face of unknown events such as flight mission changes or airframe device failures, the task adaptability of the guidance algorithm is weak

The prediction-correction guidance algorithm needs to plan a new reference flight trajectory in real time according to the flight state and terminal landing point. The task has strong adaptability, but it requires high optimization speed

However, none of the above methods consider the time-of-flight constraints, and it is necessary to study the re-entry trajectory planning and guidance algorithms especially for the time-of-flight requirements.

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