Autonomous Manipulation of an Underwater Vehicle-Manipulator System by a Composite Control Scheme With Disturbance Estimation

doi:10.1109/TASE.2023.3236149

	Autonomous Manipulation of an Underwater Vehicle-Manipulator System by a Composite Control Scheme With Disturbance Estimation
	Cai, Mingxue1 ; Wang, Yu2 ; Wang, Shuo2,3,4 ; Wang, Rui2 ; Tan, Min2,3
发表期刊	IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
ISSN	1545-5955
	2023-01-12
页码	11
通讯作者	Wang, Yu(yu.wang@ia.ac.cn)
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.
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
收录类别	SCI
语种	英语
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]
项目资助者	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)
WOS研究方向	Automation & Control Systems
WOS类目	Automation & Control Systems
WOS记录号	WOS:000921098300001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/51438
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.Chinese Univ Hong Kong CUHK, Dept Mech & Automat Engn, Hong Kong, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 4.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China
通讯作者单位	中国科学院自动化研究所
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.