Learning for Depth Control of a Robotic Penguin: A Data-Driven Model Predictive Control Approach
文献类型：期刊论文
| 作者 | Pan, Jie2; Zhang, Pengfei1,4 ; Wang, Jian4; Liu, Mingxin3; Yu, Junzhi2
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| 刊名 | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
 |
| 出版日期 | 2023-11-01 |
| 卷号 | 70期号:11页码:11422-11432 |
| ISSN号 | 0278-0046 |
| 关键词 | Data-driven model predictive control (MPC) depth control motion control reinforcement learning (RL) robotic penguin |
| DOI | 10.1109/TIE.2022.3225840 |
| 通讯作者 | Yu, Junzhi(junzhi.yu@ia.ac.cn) |
| 英文摘要 | For bionic underwater robots, it is a great challenge for depth control due to model uncertainty and strong nonlinearity. To this end, we propose a data-driven model predictive control (MPC) approach using reinforcement learning (RL) for robotic penguin depth control. First, by imitating the underwater mode of the biological penguin, a robotic prototype with a tendon-driven head, two-degrees-of-freedom wings, and a tendon-driven tail was designed. Then, a data-driven MPC framework is proposed considering the structure and motion properties of the robotic penguin. Especially, a data-based learning environment is constructed using a motion capture system, computational fluid dynamics, and a backpropagation neural network. Meanwhile, to maximize the benefits of the controller while ensuring safety and stability, a data-driven MPC using the RL scheme is applied to approximate the optimal policy. Combined with an appropriate reward design and periodic training, the closed-loop controller performance is significantly improved, and the validity of the proposed framework is finally tested by extensive simulations and experiments. Notably, this work will provide valuable insights into the learning-based motion control of bionic underwater robots. |
| 资助项目 | National Natural Science Foundation of China[62233001] ; National Natural Science Foundation of China[U1909206] ; National Natural Science Foundation of China[62073196] ; National Natural Science Foundation of China[T2121002] ; Joint Fund of Ministry of Education for Equipment PreResearch[8091B022134] ; S&T Program of Hebei[F2020203037] |
| WOS研究方向 | Automation & Control Systems ; Engineering ; Instruments & Instrumentation |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000986714600060 |
| 资助机构 | National Natural Science Foundation of China ; Joint Fund of Ministry of Education for Equipment PreResearch ; S&T Program of Hebei |
| 源URL | [http://ir.ia.ac.cn/handle/173211/53447]  |
| 专题 | 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Yu, Junzhi |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Peking Univ, Dept Adv Mfg & Robot, Coll Engn, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China 3.Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang 524088, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Pan, Jie,Zhang, Pengfei,Wang, Jian,et al. Learning for Depth Control of a Robotic Penguin: A Data-Driven Model Predictive Control Approach[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,2023,70(11):11422-11432. |
| APA | Pan, Jie,Zhang, Pengfei,Wang, Jian,Liu, Mingxin,&Yu, Junzhi.(2023).Learning for Depth Control of a Robotic Penguin: A Data-Driven Model Predictive Control Approach.IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,70(11),11422-11432. |
| MLA | Pan, Jie,et al."Learning for Depth Control of a Robotic Penguin: A Data-Driven Model Predictive Control Approach".IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 70.11(2023):11422-11432. |
入库方式： OAI收割
来源：自动化研究所
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