{"title":"Level Curve Tracking via Robust RL-Guided Model Predictive Control","authors":"Zhuo Li;Yunlong Guo;Gang Wang;Wei Chen","doi":"10.1109/JAS.2024.124350","DOIUrl":null,"url":null,"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.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 12","pages":"2512-2514"},"PeriodicalIF":15.3000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759609","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ieee-Caa Journal of Automatica Sinica","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10759609/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
The IEEE/CAA Journal of Automatica Sinica is a reputable journal that publishes high-quality papers in English on original theoretical/experimental research and development in the field of automation. The journal covers a wide range of topics including automatic control, artificial intelligence and intelligent control, systems theory and engineering, pattern recognition and intelligent systems, automation engineering and applications, information processing and information systems, network-based automation, robotics, sensing and measurement, and navigation, guidance, and control.
Additionally, the journal is abstracted/indexed in several prominent databases including SCIE (Science Citation Index Expanded), EI (Engineering Index), Inspec, Scopus, SCImago, DBLP, CNKI (China National Knowledge Infrastructure), CSCD (Chinese Science Citation Database), and IEEE Xplore.