Nonlinear model predictive position control for a tail-actuated robotic fish

doi:10.1007/s11071-020-05963-2

	Nonlinear model predictive position control for a tail-actuated robotic fish
	Zhang, Pengfei1,2 ; Wu, Zhengxing1,2 ; Meng, Yan1,2 ; Tan, Min1,2 ; Yu, Junzhi1,3
发表期刊	NONLINEAR DYNAMICS
ISSN	0924-090X
	2020-09-28
页码	13
通讯作者	Yu, Junzhi(junzhi.yu@ia.ac.cn)
摘要	Position control is a significant technique for the underwater application of robotic fish; however, it is also very challenging due to the underactuated property and input coupling of system dynamics. In this article, a two-stage orientation-velocity nonlinear model predictive controller is proposed to solve this problem. A scaled averaging model of tail-actuated robotic fish is constructed at first. Then, the novel strategy based on orientation and velocity control is developed as well as proved to be equivalent with position control in the sense of Lyapunov. Furthermore, a nonlinear model predictive controller with a two-stage switching strategy is designed to regulate the orientation and velocity error. Finally, the simulation results demonstrate the superiority of the proposed control algorithm compared with other methods. Particularly, there exists an interesting twist-braking behavior in simulation, which indicates that the proposed method makes better use of the system dynamics. The proposed method is efficient for not only bionic robotic fish but also other aquatic underactuated robots, which offers new insight into the position control of underwater robots.
关键词	Bionic robotic fish Position control Nonlinear model predictive control Underactuated dynamics
DOI	10.1007/s11071-020-05963-2
关键词[WOS]	TRACKING CONTROL ; PERFORMANCE ; DYNAMICS
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61725305] ; National Natural Science Foundation of China[61973303] ; National Natural Science Foundation of China[61633020] ; National Natural Science Foundation of China[U1909206] ; National Natural Science Foundation of China[61421004] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-JSC004]
项目资助者	National Natural Science Foundation of China ; Key Research Program of Frontier Sciences, CAS
WOS研究方向	Engineering ; Mechanics
WOS类目	Engineering, Mechanical ; Mechanics
WOS记录号	WOS:000573503000001
出版者	SPRINGER
引用统计	被引频次：11[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/173211/42017
专题	复杂系统管理与控制国家重点实验室复杂系统认知与决策实验室_先进机器人
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.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Peking Univ, Dept Mech & Engn Sci, Coll Engn, State Key Lab Turbulence & Complex Syst,BIC ESAT, Beijing 100871, Peoples R China
第一作者单位	中国科学院自动化研究所
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	Zhang, Pengfei,Wu, Zhengxing,Meng, Yan,et al. Nonlinear model predictive position control for a tail-actuated robotic fish[J]. NONLINEAR DYNAMICS,2020:13.
APA	Zhang, Pengfei,Wu, Zhengxing,Meng, Yan,Tan, Min,&Yu, Junzhi.(2020).Nonlinear model predictive position control for a tail-actuated robotic fish.NONLINEAR DYNAMICS,13.
MLA	Zhang, Pengfei,et al."Nonlinear model predictive position control for a tail-actuated robotic fish".NONLINEAR DYNAMICS (2020):13.