Self-Learning Robust Control Synthesis and Trajectory Tracking of Uncertain Dynamics

doi:10.1109/TCYB.2020.2979694

	Self-Learning Robust Control Synthesis and Trajectory Tracking of Uncertain Dynamics
	Wang, Ding1,2,3 ; Cheng, Long4,5 ; Yan, Jun 6
发表期刊	IEEE TRANSACTIONS ON CYBERNETICS
ISSN	2168-2267
	2022
卷号	52 期号:1 页码:278-286
通讯作者	Wang, Ding(dingwang@bjut.edu.cn)
摘要	In this article, we investigate the self-learning robust control synthesis and tracking design of general uncertain dynamical systems. Based on the adaptive critic learning, the robust stabilization method is developed with the help of conducting problem transformation. In addition, by considering the optimal control solution with a discounted cost function, the established method is extended to address the robust trajectory tracking design problem. The Lyapunov stability analysis is also conducted for proving the robustness of the related control plants. Finally, the simulation verification with the three case studies is provided in terms of robust stabilization and trajectory tracking, respectively.
关键词	Robust control Optimal control Cost function Trajectory tracking Nonlinear systems Feedback control Dynamical systems Adaptive critic learning control synthesis neural networks optimization robust stabilization tracking design
DOI	10.1109/TCYB.2020.2979694
关键词[WOS]	STABILIZATION
收录类别	SCI
语种	英语
资助项目	Beijing Natural Science Foundation[JQ19013] ; Beijing Natural Science Foundation[JQ19020] ; National Natural Science Foundation of China[61773373] ; National Natural Science Foundation of China[61873268] ; National Natural Science Foundation of China[U1913209] ; Natural Sciences and Engineering Research Council of Canada[RGPIN-2018-06724] ; Natural Sciences and Engineering Research Council of Canada[DGECR-2018-00022]
项目资助者	Beijing Natural Science Foundation ; National Natural Science Foundation of China ; Natural Sciences and Engineering Research Council of Canada
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:000742182700027
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：22[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/173211/47332
专题	复杂系统认知与决策实验室_先进机器人
通讯作者	Wang, Ding
作者单位	1.Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China 2.Beijing Univ Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China 3.Beijing Univ Technol, Beijing Artificial Intelligence Inst, Beijing 100124, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 6.Concordia Univ, Concordia Inst Informat Syst Engn, Montreal, PQ H3G 1M8, Canada
推荐引用方式 GB/T 7714	Wang, Ding,Cheng, Long,Yan, Jun. Self-Learning Robust Control Synthesis and Trajectory Tracking of Uncertain Dynamics[J]. IEEE TRANSACTIONS ON CYBERNETICS,2022,52(1):278-286.
APA	Wang, Ding,Cheng, Long,&Yan, Jun.(2022).Self-Learning Robust Control Synthesis and Trajectory Tracking of Uncertain Dynamics.IEEE TRANSACTIONS ON CYBERNETICS,52(1),278-286.
MLA	Wang, Ding,et al."Self-Learning Robust Control Synthesis and Trajectory Tracking of Uncertain Dynamics".IEEE TRANSACTIONS ON CYBERNETICS 52.1(2022):278-286.