Tight-Space Maneuvering of a Hybrid-Driven Robotic Fish Using Backstepping-Based Adaptive Control

doi:10.1109/TMECH.2023.3338879

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	Tight-Space Maneuvering of a Hybrid-Driven Robotic Fish Using Backstepping-Based Adaptive Control
	Li, Sijie 1,2; Wu, Zhengxing 1,2; Dai, Shijie 1,2; Wang, Jian 1,2; Tan, Min 1,2; Yu, Junzhi 2,3
刊名	IEEE-ASME TRANSACTIONS ON MECHATRONICS
	2023-12-15
页码	13
关键词	Robots Propellers Robot kinematics Robot sensing systems Propulsion Mechatronics Hydrodynamics 3-D path following backstepping-based adaptive control depth control hybrid drive robotic fish
ISSN号	1083-4435
DOI	10.1109/TMECH.2023.3338879
通讯作者	Wu, Zhengxing()
英文摘要	Precise path-following control in tight space is a great challenge for underwater operation. To this end, this article proposes a 3-D path-following control system for a miniature robotic fish. Aiming at achieving higher maneuverability, a newly designed miniature hybrid-driven robotic fish is presented for maneuvering in a tight space, owning both fish-like and propeller-based motion modes. On this basis, a novel 3-D path-following control framework is proposed, including a navigation strategy, a depth controller, a heading controller, and a nonlinear mapping process, ensuring reliable 3-D path-following performance. More importantly, a gliding-oscillating-strategy-based backstepping-adaptive control method is provided to attenuate the jitter of the tracking error, which exhibits both low sensitivity to the hydrodynamic parameters and ideal match to the 3-D path tracking of a single-jointed robotic fish. Extensive comparative simulations and aquatic experiments are carried out, e.g., flexible swimming among obstacles in tight space and 3-D path-following tasks with imprecise hydrodynamic parameters. The obtained results verify the effectiveness of the designed prototype and the proposed methods, providing valuable insight for the new-type underwater platform design and underwater operations in tight space.
资助项目	National Natural Science Foundation of China
WOS关键词	MOMENT ; DRAG
WOS研究方向	Automation & Control Systems ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:001130331100001
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54985]
专题	复杂系统认知与决策实验室
通讯作者	Wu, Zhengxing
作者单位	1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, Lab Cognit & Decis Intelligence Complex Syst, Beijing 100190, Peoples R China 3.Peking Univ, Dept Adv Mfg & Robot, State Key Lab Turbulence & Complex Syst, BIC ESAT,Coll Engn, Beijing 100871, Peoples R China
推荐引用方式 GB/T 7714	Li, Sijie,Wu, Zhengxing,Dai, Shijie,et al. Tight-Space Maneuvering of a Hybrid-Driven Robotic Fish Using Backstepping-Based Adaptive Control[J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS,2023:13.
APA	Li, Sijie,Wu, Zhengxing,Dai, Shijie,Wang, Jian,Tan, Min,&Yu, Junzhi.(2023).Tight-Space Maneuvering of a Hybrid-Driven Robotic Fish Using Backstepping-Based Adaptive Control.IEEE-ASME TRANSACTIONS ON MECHATRONICS,13.
MLA	Li, Sijie,et al."Tight-Space Maneuvering of a Hybrid-Driven Robotic Fish Using Backstepping-Based Adaptive Control".IEEE-ASME TRANSACTIONS ON MECHATRONICS (2023):13.