Level Curve Tracking via Robust RL-Guided Model Predictive Control

Dear Editor, This letter investigates the level curve tracking problem of unknown scalar fields using an unmanned aerial vehicle (UAV) and presents a robust reinforcement learning (RL)-guided model predictive control (MPC) scheme for the UAV. Specifically, we formulate the MPC trajectory tracking problem, wherein an RL-based trajectory planning algorithm provides the reference trajectory to guide the UAV towards the desired concentration. Notably, we introduce random noise during the training of the planning policy in the RL algorithm, demonstrating its efficacy in enhancing policy robustness. The proposed RL-guided MPC scheme's effectiveness is validated through simulations.

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Publication Details

Journal
IEEE/CAA Journal of Automatica Sinica
Published
2024-11-20
DOI
https://doi.org/10.1109/jas.2024.124350
Citations
3
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
0.98

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article

Level Curve Tracking via Robust RL-Guided Model Predictive Control

Yunlong Guo, Zhuo Li, Gang Wang, Wei Chen
3 citations
IEEE/CAA Journal of Automatica Sinica
Advanced Control Systems Optimization
0.98
article

Level Curve Tracking via Robust RL-Guided Model Predictive Control

Yunlong Guo, Zhuo Li, Gang Wang, Wei Chen
article en
3 citations

Abstract

Dear Editor, This letter investigates the level curve tracking problem of unknown scalar fields using an unmanned aerial vehicle (UAV) and presents a robust reinforcement learning (RL)-guided model predictive control (MPC) scheme for the UAV. Specifically, we formulate the MPC trajectory tracking problem, wherein an RL-based trajectory planning algorithm provides the reference trajectory to guide the UAV towards the desired concentration. Notably, we introduce random noise during the training of the planning policy in the RL algorithm, demonstrating its efficacy in enhancing policy robustness. The proposed RL-guided MPC scheme's effectiveness is validated through simulations.

IEEE/CAA Journal of Automatica SinicaVol. 11(12)
Beijing Institute of Technology (CN), Chongqing University of Technology (CN)
National Natural Science Foundation of China, Science and Technology Major Project of Guangxi
Climate action
Openalex Percentile: Top 23%
Advanced Control Systems Optimization
0.98
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Level Curve Tracking via Robust RL-Guided Model Predictive Control — Yunlong Guo, Zhuo Li, et al. · IEEE/CAA Journal of Automatica Sinica (2024) | TGRS Research Map | TGRS