Incentive Stackelberg game for H∞-constrained multi-hierarchy systems under observation information
Incentive Stackelberg game for H∞-constrained multi-hierarchy systems under observation information
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DOI：
10.1049/cth2.12348
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Zhongjin Guo
中科院分区：
文献类型：
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作者：
Xiaoqian Li;Mengyu Bai;Huanshui Zhang;Zonglei Jing;Peijun Ju;Zhongjin Guo
This paper considers the incentive feedback Stackelberg game with multi-hierarchy players under a H∞ constraint, with the proposed solution involving nested hierarchies A and B. In hierarchy A, P0 represents the leader (the leader’s control input corresponding to i-th follower, i = 1, 2,…, n), and P1,…, Pn are the followers, with non-cooperative followers induced to virtually cooperate in achieving team-optimal solution and the Nash equilibrium. In hierarchy B, the external disturbance represents the follower, and hierarchy A represents the leader. The main contributions of this work are three-fold. First, an incentive Stackelberg strategy set under the H∞ constraint through observation information is obtained for the first time. Second, a novel iterative algorithm to solve the coupled backward and forward Riccati equations is introduced and thus obtaining an explicit expression of a team-optimal feedback Stackelberg strategy set with an H∞ constraint. Finally, the necessary and sufficient conditions for the existence and uniqueness of the hierarchical game’s optimal solutions using the Lyapunov equation and the induction algorithm are presented.
