Decentralized robust zero-sum neuro-optimal control for modular robot manipulators in contact with uncertain environments: theory and experimental verification

doi:10.1007/s11071-019-04994-8

	Decentralized robust zero-sum neuro-optimal control for modular robot manipulators in contact with uncertain environments: theory and experimental verification
	Dong, Bo1,2 ; An, Tianjiao 1; Zhou, Fan 1; Liu, Keping 1; Li, Yuanchun 1
刊名	NONLINEAR DYNAMICS
	2019-07-01
卷号	97 期号:1 页码:503-524
关键词	Modular robot manipulators Adaptive dynamic programming Decentralized control Optimal control Zero-sum game
ISSN号	0924-090X
DOI	10.1007/s11071-019-04994-8
通讯作者	Li, Yuanchun(liyc@ccut.edu.cn)
英文摘要	This paper presents a decentralized robust zero-sum optimal control approach for modular robot manipulators (MRMs) in contact with uncertain environments based on the adaptive dynamic programming (ADP) algorithm. The dynamic model of MRMs is formulated via joint torque feedback technique that is deployed for each joint module to design the model compensation controller. An uncertainty decomposition-based robust control is developed to compensate the model uncertainties, and then, the robust optimal control problem of the MRM system is transformed into a two-player zero-sum optimal control one. According to the ADP algorithm, the Hamilton-Jacobi-Isaacs equation can be solved by establishing action and critic neural networks, thus making the derivation of the approximate optimal control policy feasible. Based on the Lyapunov theory, the closed-loop robotic system is proved to be asymptotic stable under the developed decentralized control method. Finally, experiments are conducted to verify the effectiveness and advantages of the proposed method.
资助项目	National Natural Science Foundation of China[61374051] ; National Natural Science Foundation of China[61773075] ; National Natural Science Foundation of China[61703055] ; Scientific Technological Development Plan Project in Jilin Province of China[20170204067GX] ; Scientific Technological Development Plan Project in Jilin Province of China[20160520013JH] ; Scientific Technological Development Plan Project in Jilin Province of China[2016041403-3GH] ; Science and Technology Project of Jilin Provincial Education Department of China[JJKH20170569KJ]
WOS关键词	NONLINEAR-SYSTEMS ; POLICY ITERATION ; TORQUE SENSOR ; STABILIZATION ; COMPENSATION ; CONVERGENCE ; POSITION ; NETWORK ; DESIGN ; INPUT
WOS研究方向	Engineering ; Mechanics
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000473520700031
资助机构	National Natural Science Foundation of China ; Scientific Technological Development Plan Project in Jilin Province of China ; Science and Technology Project of Jilin Provincial Education Department of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/26864]
专题	中国科学院自动化研究所
通讯作者	Li, Yuanchun
作者单位	1.Changchun Univ Technol, Dept Control Sci & Engn, Changchun 130012, Jilin, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Dong, Bo,An, Tianjiao,Zhou, Fan,et al. Decentralized robust zero-sum neuro-optimal control for modular robot manipulators in contact with uncertain environments: theory and experimental verification[J]. NONLINEAR DYNAMICS,2019,97(1):503-524.
APA	Dong, Bo,An, Tianjiao,Zhou, Fan,Liu, Keping,&Li, Yuanchun.(2019).Decentralized robust zero-sum neuro-optimal control for modular robot manipulators in contact with uncertain environments: theory and experimental verification.NONLINEAR DYNAMICS,97(1),503-524.
MLA	Dong, Bo,et al."Decentralized robust zero-sum neuro-optimal control for modular robot manipulators in contact with uncertain environments: theory and experimental verification".NONLINEAR DYNAMICS 97.1(2019):503-524.