自主学习干扰观测器驱动的重复使用运载器再入段滑模控制

Jia Ye Chen; Rong Jun Mu; Yu Liang Bai; Xin Zhang; Nai Gang Cui

doi:10.3873/j.issn.1000-1328.2019.06.010

自主学习干扰观测器驱动的重复使用运载器再入段滑模控制

Translated title of the contribution: Sliding Mode Control in Reentry Phase for a Reusable Launch Vehicle Driven by a Self-Learning Disturbance Observer

Jia Ye Chen
, Rong Jun Mu^*
, Yu Liang Bai
, Xin Zhang
, Nai Gang Cui

^*Corresponding author for this work

School of Astronautics

Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

A sliding mode controller based on self-learning disturbance observer (SLDO) is designed for a reusable launch vehicle (RLV). According to the singular perturbation theory, a RLV dynamic model is divided into the outer-loop and inner-loop subsystems. Since the model uncertainties and the disturbances vary with time and have unknown boundaries, combining with the type-2 neuro-fuzzy structure, feedback-error learning scheme and sliding mode control (SMC) theory, a novel online SLDO is presented. The multivariable supertwisting sliding mode controller driven by a SLDO is designed to track the re-entry trajectory precisely and convergent rapidly. Finally, by the simulation and analysis of the 6-degree-of-freedom model of RLV in the reentry phase, the effectiveness and the robustness of the integrated control scheme are verified.

Translated title of the contribution	Sliding Mode Control in Reentry Phase for a Reusable Launch Vehicle Driven by a Self-Learning Disturbance Observer
Original language	Chinese (Traditional)
Pages (from-to)	694-702
Number of pages	9
Journal	Yuhang Xuebao/Journal of Astronautics
Volume	40
Issue number	6
DOIs	https://doi.org/10.3873/j.issn.1000-1328.2019.06.010
State	Published - 30 Jun 2019

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@article{b71cd32873544035bf50df9b50627e41,

title = "自主学习干扰观测器驱动的重复使用运载器再入段滑模控制",

abstract = "A sliding mode controller based on self-learning disturbance observer (SLDO) is designed for a reusable launch vehicle (RLV). According to the singular perturbation theory, a RLV dynamic model is divided into the outer-loop and inner-loop subsystems. Since the model uncertainties and the disturbances vary with time and have unknown boundaries, combining with the type-2 neuro-fuzzy structure, feedback-error learning scheme and sliding mode control (SMC) theory, a novel online SLDO is presented. The multivariable supertwisting sliding mode controller driven by a SLDO is designed to track the re-entry trajectory precisely and convergent rapidly. Finally, by the simulation and analysis of the 6-degree-of-freedom model of RLV in the reentry phase, the effectiveness and the robustness of the integrated control scheme are verified.",

keywords = "Reentry attitude track, Reusable launch vehicle (RLV), Self-learning disturbance observer (SLDO), Sliding mode control (SMC)",

author = "Chen, \{Jia Ye\} and Mu, \{Rong Jun\} and Bai, \{Yu Liang\} and Xin Zhang and Cui, \{Nai Gang\}",

year = "2019",

month = jun,

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doi = "10.3873/j.issn.1000-1328.2019.06.010",

language = "繁体中文",

volume = "40",

pages = "694--702",

journal = "Yuhang Xuebao/Journal of Astronautics",

issn = "1000-1328",

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T1 - 自主学习干扰观测器驱动的重复使用运载器再入段滑模控制

AU - Chen, Jia Ye

AU - Mu, Rong Jun

AU - Bai, Yu Liang

AU - Zhang, Xin

AU - Cui, Nai Gang

PY - 2019/6/30

Y1 - 2019/6/30

N2 - A sliding mode controller based on self-learning disturbance observer (SLDO) is designed for a reusable launch vehicle (RLV). According to the singular perturbation theory, a RLV dynamic model is divided into the outer-loop and inner-loop subsystems. Since the model uncertainties and the disturbances vary with time and have unknown boundaries, combining with the type-2 neuro-fuzzy structure, feedback-error learning scheme and sliding mode control (SMC) theory, a novel online SLDO is presented. The multivariable supertwisting sliding mode controller driven by a SLDO is designed to track the re-entry trajectory precisely and convergent rapidly. Finally, by the simulation and analysis of the 6-degree-of-freedom model of RLV in the reentry phase, the effectiveness and the robustness of the integrated control scheme are verified.

AB - A sliding mode controller based on self-learning disturbance observer (SLDO) is designed for a reusable launch vehicle (RLV). According to the singular perturbation theory, a RLV dynamic model is divided into the outer-loop and inner-loop subsystems. Since the model uncertainties and the disturbances vary with time and have unknown boundaries, combining with the type-2 neuro-fuzzy structure, feedback-error learning scheme and sliding mode control (SMC) theory, a novel online SLDO is presented. The multivariable supertwisting sliding mode controller driven by a SLDO is designed to track the re-entry trajectory precisely and convergent rapidly. Finally, by the simulation and analysis of the 6-degree-of-freedom model of RLV in the reentry phase, the effectiveness and the robustness of the integrated control scheme are verified.

KW - Reentry attitude track

KW - Reusable launch vehicle (RLV)

KW - Self-learning disturbance observer (SLDO)

KW - Sliding mode control (SMC)

UR - https://www.scopus.com/pages/publications/85072175054

U2 - 10.3873/j.issn.1000-1328.2019.06.010

DO - 10.3873/j.issn.1000-1328.2019.06.010

M3 - 文章

AN - SCOPUS:85072175054

SN - 1000-1328

VL - 40

SP - 694

EP - 702

JO - Yuhang Xuebao/Journal of Astronautics

JF - Yuhang Xuebao/Journal of Astronautics

IS - 6

ER -

自主学习干扰观测器驱动的重复使用运载器再入段滑模控制

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