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

文献类型：期刊论文

作者Wang, Ding1,5,6; Cheng, Long3,4; Yan, Jun2
刊名IEEE TRANSACTIONS ON CYBERNETICS
出版日期2022
卷号52期号:1页码:278-286
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
ISSN号2168-2267
DOI10.1109/TCYB.2020.2979694
通讯作者Wang, Ding(dingwang@bjut.edu.cn)
英文摘要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.
WOS关键词STABILIZATION
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]
WOS研究方向Automation & Control Systems ; Computer Science
语种英语
WOS记录号WOS:000742182700027
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构Beijing Natural Science Foundation ; National Natural Science Foundation of China ; Natural Sciences and Engineering Research Council of Canada
源URL[http://ir.ia.ac.cn/handle/173211/47331]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者Wang, Ding
作者单位1.Beijing Univ Technol, Beijing Artificial Intelligence Inst, Beijing 100124, Peoples R China
2.Concordia Univ, Concordia Inst Informat Syst Engn, Montreal, PQ H3G 1M8, Canada
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
5.Beijing Univ Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China
6.Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
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.

入库方式： OAI收割

来源：自动化研究所

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