Autonomous Manipulation of an Underwater Vehicle-Manipulator System by a Composite Control Scheme With Disturbance Estimation
文献类型：期刊论文
| 作者 | Cai, Mingxue4 ; Wang, Yu3; Wang, Shuo1,2,3; Wang, Rui3; Tan, Min2,3
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| 刊名 | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
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| 出版日期 | 2023-01-12 |
| 页码 | 11 |
| ISSN号 | 1545-5955 |
| 关键词 | Predictive models Vehicle dynamics Optimal control Load modeling Uncertainty Solid modeling Predictive control Underwater vehicle-manipulator system (UVMS) disturbance observer (DOB) nonlinear model predictive control (NMPC) autonomous underwater manipulation |
| DOI | 10.1109/TASE.2023.3236149 |
| 通讯作者 | Wang, Yu(yu.wang@ia.ac.cn) |
| 英文摘要 | This article addresses an autonomous manipulation problem for an underwater vehicle-manipulator system (UVMS) operating in a free-floating way while subjecting to unknown continuous disturbance. More specifically, a composite control scheme composed of disturbance observer (DOB), predictor model network (PM-Net), and nonlinear model predictive control (NMPC), is devised to improve the control performance of UVMS (i.e., unicycle-like UVMS actuated only in the surge, heave, and yaw for vehicle body) in the case of disturbance, model mismatch, and input saturation. A RBF-DOB is formulated by combining a DOB and a Radial Basis Function (RBF) neural network to estimate disturbance at the current step. Then, the PM-Network, composed of a disturbance predictor network and state predictor network, is developed based on long short-term memory (LSTM) network that predicts UVMS state sequences considering model mismatch and disturbance. The NMPC is deployed as a feedback control law to endow the input saturation of the UVMS and produce optimal control action. Compared with conventional DOB control methods using feed-forward compensation of disturbance, the primary merit of the proposed approach is that the disturbance estimated by RBF-DOB is utilized in the PM-Net to predict future UVMS state sequences, which are exploited on the NMPC's receding optimization. RGB0,0,0Finally, realistic simulation and relevant experiment are conducted to demonstrate the effectiveness of the proposed method. Note to Practitioners-The motivation behind this article is the autonomous manipulation of an underwater vehicle-manipulator system subjected to unknown disturbance. However, it is not always feasible or straightforward to obtain the external disturbance and unmodeled dynamics for designing robust controllers. On the one hand, how to manipulate the disturbance into the designed controller to generate optimal control action rather than by using feed-forward compensation. On the other hand, the control input saturation often occurs in the UVMS control, especially under the disturbance rejection conditions, where it should be considered in the controller design. Currently, the predominant methods for UVMS control lack a control scheme that provides a complete and credible control strategy that takes the aforementioned issues into consideration. Motivated by the above analysis, this study provides a composite control scheme to deal with the dynamic uncertainties, unknown disturbance, and input saturation. RGB0,0,0The results of realistic simulation and relevant experiments demonstrate the effectiveness of the proposed method. Hopefully, our control method can provide valuable theoretical and technical guidance to practicing marine engineers for controller design. |
| 资助项目 | National Natural Science Foundation of China[62122087] ; National Natural Science Foundation of China[62073316] ; National Natural Science Foundation of China[62033013] ; Youth Innovation Promotion Association Chinese Academy of Sciences (CAS) ; Beijing Natural Science Foundation[4222055] ; Beijing Natural Science Foundation[4222056] ; Scientific Research Program of Beijing Municipal Commission of Education-Natural Science Foundation of Beijing[KZ202210017024] ; Beijing Nova Program[Z211100002121152] ; Young Elite Scientist Sponsorship Program by the China Association for Science and Technology (CAST)[YESS20210236] |
| WOS研究方向 | Automation & Control Systems |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000921098300001 |
| 资助机构 | National Natural Science Foundation of China ; Youth Innovation Promotion Association Chinese Academy of Sciences (CAS) ; Beijing Natural Science Foundation ; Scientific Research Program of Beijing Municipal Commission of Education-Natural Science Foundation of Beijing ; Beijing Nova Program ; Young Elite Scientist Sponsorship Program by the China Association for Science and Technology (CAST) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/51437]  |
| 专题 | 多模态人工智能系统全国重点实验室 复杂系统认知与决策实验室 |
| 通讯作者 | Wang, Yu |
| 作者单位 | 1.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence, Beijing 100190, Peoples R China 4.Chinese Univ Hong Kong CUHK, Dept Mech & Automat Engn, Hong Kong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cai, Mingxue,Wang, Yu,Wang, Shuo,et al. Autonomous Manipulation of an Underwater Vehicle-Manipulator System by a Composite Control Scheme With Disturbance Estimation[J]. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,2023:11. |
| APA | Cai, Mingxue,Wang, Yu,Wang, Shuo,Wang, Rui,&Tan, Min.(2023).Autonomous Manipulation of an Underwater Vehicle-Manipulator System by a Composite Control Scheme With Disturbance Estimation.IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,11. |
| MLA | Cai, Mingxue,et al."Autonomous Manipulation of an Underwater Vehicle-Manipulator System by a Composite Control Scheme With Disturbance Estimation".IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2023):11. |
入库方式： OAI收割
来源：自动化研究所
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