arrow
Return

Entry Guidance With No-Fly Zone Avoidance Using Linear Pseudospectral Model Predictive Control

delete2019-01-01
delete8
delete
OA
AI
杨良 (Liang Yang)
J
Jin Yang
W
Wanchun Chen *
H
Hao Liu
DOI:10.1109/ACCESS.2019.2927995delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
This paper presents an efficient entry guidance law for no-fly zone avoidance, which is based on the recently developed linear pseudospectral model predictive control. First, a simple mapping relation of the position of the no-fly zone between the inertial frame (IF) and the auxiliary geographical frame (AGI) is derived in a geometric manner. Second, a model predictive method is used to judge whether the constraint of the no-fly zone is activated in AGI. Then, additional bank reversal is performed to shape the entry trajectory at the right time so as to avoid the no-fly zone. This method is very easy to be implemented onboard and does not increase the additional computational burden. The nominal and Monte Carlo simulations are conducted to show that the proposed method consistently offers very great, stable, and robust performances.
Keywords:
Autonomous no-fly zone avoidance
entry guidance
linear pseudospectral model predictive control
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

B
Beihang University
Scholars:
5.2W
Papers: 4.1W
Citations: 37