中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Hierarchical optimal control for input-affine nonlinear systems through the formulation of Stackelberg game

文献类型:期刊论文

作者Mu, Chaoxu1; Wang, Ke1; Zhang, Qichao2,3; Zhao, Dongbin2,3
刊名INFORMATION SCIENCES
出版日期2020-05-01
卷号517页码:1-17
ISSN号0020-0255
关键词Nonzero-sum differential game Hierarchical optimization Nonlinear dynamics Stackelberg equilibrium Neural network
DOI10.1016/j.ins.2019.12.078
通讯作者Mu, Chaoxu(cxmu@tju.edu.cn)
英文摘要Substantial efforts have been undertaken to explore nonzero-sum differential games. Most of these studies are devoted to devising algorithms to pursue Nash equilibrium, where all players with the same access to information will take policies synchronously. However, when it comes to hierarchical optimization and asymmetric information, Nash equilibrium is ineffective. The Stackelberg game provides us with an idea of leader-follower strategy to cope with this conundrum. The paper investigates hierarchical optimal control for continuous-time two-player input-affine systems characterized by nonlinear dynamics and quadratic cost functions. By introducing new costates, this optimization problem is formulated as a Stackelberg game in conjunction with a parametric optimization problem. Besides, the closed-loop information is available for both players. An adaptive learning algorithm is thus developed to approximately obtain the open-loop Stackelberg equilibrium while ensuring the uniform ultimate bounded stability of this closed-loop system, and two approximators structured by neural networks put this purpose into practice. Finally, two numerical examples illustrate that the proposed methodology can accurately obtain optimal solutions, and a comparative example illustrates its characteristics. (C) 2020 Elsevier Inc. All rights reserved.
WOS关键词STRATEGIES ; ALGORITHM
资助项目National Natural Science Foundation of China[61773284] ; National Natural Science Foundation of China[61803371] ; National Natural Science Foundation of China[61533017]
WOS研究方向Computer Science
语种英语
出版者ELSEVIER SCIENCE INC
WOS记录号WOS:000517659200001
资助机构National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/38382]  
专题复杂系统管理与控制国家重点实验室_深度强化学习
通讯作者Mu, Chaoxu
作者单位1.Tianjin Univ, Sch Elect & Informat Engn, Tianjin 300072, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.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
Mu, Chaoxu,Wang, Ke,Zhang, Qichao,et al. Hierarchical optimal control for input-affine nonlinear systems through the formulation of Stackelberg game[J]. INFORMATION SCIENCES,2020,517:1-17.
APA Mu, Chaoxu,Wang, Ke,Zhang, Qichao,&Zhao, Dongbin.(2020).Hierarchical optimal control for input-affine nonlinear systems through the formulation of Stackelberg game.INFORMATION SCIENCES,517,1-17.
MLA Mu, Chaoxu,et al."Hierarchical optimal control for input-affine nonlinear systems through the formulation of Stackelberg game".INFORMATION SCIENCES 517(2020):1-17.

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