Prescribed performance-based powered descent guidance for step-shaped hazardous terrains
Prescribed performance-based powered descent guidance for step-shaped hazardous terrains
The planetary powered descent guidance problem for step-shaped hazardous terrains is investigated in this article based on prescribed performance function (PPF) methodology. Initially, the distances between the lander and step-shaped terrains around the landing site have been formulated in a new form boundaryfunction using PPF, in which a new step-shaped boundary PPF is specifically designed to constrain the lateral motion. Furthermore, a fixed-time convergent PPF is chosen to coordinate the vertical motion. Next, to avoid the collision with step-shaped terrains and planetary surface, a feedback guidance algorithm is proposed based on the backstepping method. Considering a large guidance gain is beneficial for the lander to move away from the boundary PPF, but excessive control acceleration will be generated when the landing error is large. To solve this problem, an adaptive guidance gain is designed using Gaussian function. Finally, the feasibility and effectiveness of the proposed algorithm have been verified through typical numerical simulations inspired by realistic Martian terrains. Moreover, this attempt using PPF methodology here can be easily reformulated to adjust the powered descent problem with collision avoidance for a flat surface or glide-slope constraint.
Adaptive gain, collision avoidance, feedback guidance, powered descent phase, prescribed performance
1083-1095
Gong, Youmin
b773ae52-6da4-4e57-bb7d-21fcb0082dfa
Guo, Yanning
8c00e47f-af8f-4897-97ea-06160d66a914
Ma, Guangfu
ac87dc64-00bf-41c8-b72a-dabb584da67a
Zhang, Yao
a4f30318-ab42-4b38-a60d-f7199ff3a02a
Guo, Minwen
bd769f54-fb19-4385-ab31-cd180c2901b7
1 April 2022
Gong, Youmin
b773ae52-6da4-4e57-bb7d-21fcb0082dfa
Guo, Yanning
8c00e47f-af8f-4897-97ea-06160d66a914
Ma, Guangfu
ac87dc64-00bf-41c8-b72a-dabb584da67a
Zhang, Yao
a4f30318-ab42-4b38-a60d-f7199ff3a02a
Guo, Minwen
bd769f54-fb19-4385-ab31-cd180c2901b7
Gong, Youmin, Guo, Yanning, Ma, Guangfu, Zhang, Yao and Guo, Minwen
(2022)
Prescribed performance-based powered descent guidance for step-shaped hazardous terrains.
IEEE Transactions on Aerospace and Electronic Systems, 58 (2), .
(doi:10.1109/TAES.2021.3117094).
Abstract
The planetary powered descent guidance problem for step-shaped hazardous terrains is investigated in this article based on prescribed performance function (PPF) methodology. Initially, the distances between the lander and step-shaped terrains around the landing site have been formulated in a new form boundaryfunction using PPF, in which a new step-shaped boundary PPF is specifically designed to constrain the lateral motion. Furthermore, a fixed-time convergent PPF is chosen to coordinate the vertical motion. Next, to avoid the collision with step-shaped terrains and planetary surface, a feedback guidance algorithm is proposed based on the backstepping method. Considering a large guidance gain is beneficial for the lander to move away from the boundary PPF, but excessive control acceleration will be generated when the landing error is large. To solve this problem, an adaptive guidance gain is designed using Gaussian function. Finally, the feasibility and effectiveness of the proposed algorithm have been verified through typical numerical simulations inspired by realistic Martian terrains. Moreover, this attempt using PPF methodology here can be easily reformulated to adjust the powered descent problem with collision avoidance for a flat surface or glide-slope constraint.
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More information
e-pub ahead of print date: 18 October 2021
Published date: 1 April 2022
Keywords:
Adaptive gain, collision avoidance, feedback guidance, powered descent phase, prescribed performance
Identifiers
Local EPrints ID: 471560
URI: http://eprints.soton.ac.uk/id/eprint/471560
ISSN: 0018-9251
PURE UUID: 9f92bc0c-256c-414e-a743-a697f5680b84
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Date deposited: 11 Nov 2022 17:34
Last modified: 17 Mar 2024 04:14
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Author:
Youmin Gong
Author:
Yanning Guo
Author:
Guangfu Ma
Author:
Yao Zhang
Author:
Minwen Guo
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