CACLA-Based Trajectory Tracking Guidance for RLV in Terminal Area Energy Management Phase
This paper focuses on the trajectory tracking guidance problem for the Terminal Area Energy Management (TAEM) phase of the Reusable Launch Vehicle (RLV). Considering the continuous state and action space of this guidance problem, the Continuous Actor–Critic Learning Automata (CACLA) is applied to co...
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Format: | Article |
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MDPI AG
2021-07-01
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Series: | Sensors |
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Online Access: | https://www.mdpi.com/1424-8220/21/15/5062 |
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author | Xuejing Lan Zhifeng Tan Tao Zou Wenbiao Xu |
author_facet | Xuejing Lan Zhifeng Tan Tao Zou Wenbiao Xu |
author_sort | Xuejing Lan |
collection | DOAJ |
description | This paper focuses on the trajectory tracking guidance problem for the Terminal Area Energy Management (TAEM) phase of the Reusable Launch Vehicle (RLV). Considering the continuous state and action space of this guidance problem, the Continuous Actor–Critic Learning Automata (CACLA) is applied to construct the guidance strategy of RLV. Two three-layer neuron networks are used to model the critic and actor of CACLA, respectively. The weight vectors of the critic are updated by the model-free Temporal Difference (TD) learning algorithm, which is improved by eligibility trace and momentum factor. The weight vectors of the actor are updated based on the sign of TD error, and a Gauss exploration is carried out in the actor. Finally, a Monte Carlo simulation and a comparison simulation are performed to show the effectiveness of the CACLA-based guidance strategy. |
first_indexed | 2024-03-10T09:09:37Z |
format | Article |
id | doaj.art-e7e7fcacc14b4867b0de653a9a174aed |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-03-10T09:09:37Z |
publishDate | 2021-07-01 |
publisher | MDPI AG |
record_format | Article |
series | Sensors |
spelling | doaj.art-e7e7fcacc14b4867b0de653a9a174aed2023-11-22T06:09:53ZengMDPI AGSensors1424-82202021-07-012115506210.3390/s21155062CACLA-Based Trajectory Tracking Guidance for RLV in Terminal Area Energy Management PhaseXuejing Lan0Zhifeng Tan1Tao Zou2Wenbiao Xu3School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, ChinaSchool of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, ChinaSchool of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, ChinaGuangdong Province Institute of Metrology, Guangzhou 510450, ChinaThis paper focuses on the trajectory tracking guidance problem for the Terminal Area Energy Management (TAEM) phase of the Reusable Launch Vehicle (RLV). Considering the continuous state and action space of this guidance problem, the Continuous Actor–Critic Learning Automata (CACLA) is applied to construct the guidance strategy of RLV. Two three-layer neuron networks are used to model the critic and actor of CACLA, respectively. The weight vectors of the critic are updated by the model-free Temporal Difference (TD) learning algorithm, which is improved by eligibility trace and momentum factor. The weight vectors of the actor are updated based on the sign of TD error, and a Gauss exploration is carried out in the actor. Finally, a Monte Carlo simulation and a comparison simulation are performed to show the effectiveness of the CACLA-based guidance strategy.https://www.mdpi.com/1424-8220/21/15/5062RLVguidanceTAEMCACLATD learning |
spellingShingle | Xuejing Lan Zhifeng Tan Tao Zou Wenbiao Xu CACLA-Based Trajectory Tracking Guidance for RLV in Terminal Area Energy Management Phase Sensors RLV guidance TAEM CACLA TD learning |
title | CACLA-Based Trajectory Tracking Guidance for RLV in Terminal Area Energy Management Phase |
title_full | CACLA-Based Trajectory Tracking Guidance for RLV in Terminal Area Energy Management Phase |
title_fullStr | CACLA-Based Trajectory Tracking Guidance for RLV in Terminal Area Energy Management Phase |
title_full_unstemmed | CACLA-Based Trajectory Tracking Guidance for RLV in Terminal Area Energy Management Phase |
title_short | CACLA-Based Trajectory Tracking Guidance for RLV in Terminal Area Energy Management Phase |
title_sort | cacla based trajectory tracking guidance for rlv in terminal area energy management phase |
topic | RLV guidance TAEM CACLA TD learning |
url | https://www.mdpi.com/1424-8220/21/15/5062 |
work_keys_str_mv | AT xuejinglan caclabasedtrajectorytrackingguidanceforrlvinterminalareaenergymanagementphase AT zhifengtan caclabasedtrajectorytrackingguidanceforrlvinterminalareaenergymanagementphase AT taozou caclabasedtrajectorytrackingguidanceforrlvinterminalareaenergymanagementphase AT wenbiaoxu caclabasedtrajectorytrackingguidanceforrlvinterminalareaenergymanagementphase |