论文标题

Minmax的领导者追随者网络的均值球队方法:鞍点策略

MinMax Mean-Field Team Approach for a Leader-Follower Network: A Saddle-Point Strategy

论文作者

Baharloo, Mohammad M., Arabneydi, Jalal, Aghdam, Amir G.

论文摘要

本文研究了领导者追随者网络的软件限制的Minmax控制问题。该网络由一个领导者和希望达成共识的任意追随者,在存在外部干扰的情况下,最少的能源消耗。领导者和追随者在动态和成本功能中耦合。考虑了两个非古典信息结构:平均场共享和间歇性平均场共享,均值场是指追随者的总体状态。在平均场所共享中,每个追随者都观察其地方状态,领导者状态和平均领域,而在间歇性平均场共享中,仅在某些(可能是)(可能是)时刻观察到平均场。定义了社会福利成本功能,并表明存在一种独特的鞍策略,它可以最大程度地减少均值场共享信息结构下的成本函数最差的价值。该溶液是通过两个可伸缩的Riccati方程获得的,该方程取决于规定的衰减参数,作为鲁棒性因子。对于间歇性平均场共享信息结构,提出了近似的鞍点策略,并分析了其收敛到马鞍点的策略。提供了两个数值示例,以证明获得的结果的功效。

This paper investigates a soft-constrained MinMax control problem of a leader-follower network. The network consists of one leader and an arbitrary number of followers that wish to reach consensus with minimum energy consumption in the presence of external disturbances. The leader and followers are coupled in the dynamics and cost function. Two non-classical information structures are considered: mean-field sharing and intermittent mean-field sharing, where the mean-field refers to the aggregate state of the followers. In mean-field sharing, every follower observes its local state, the state of the leader and the mean field while in the intermittent mean-field sharing, the mean-field is only observed at some (possibly no) time instants. A social welfare cost function is defined, and it is shown that a unique saddle-point strategy exists which minimizes the worst-case value of the cost function under mean-field sharing information structure. The solution is obtained by two scalable Riccati equations, which depend on a prescribed attenuation parameter, serving as a robustness factor. For the intermittent mean-field sharing information structure, an approximate saddle-point strategy is proposed, and its converges to the saddle-point is analyzed. Two numerical examples are provided to demonstrate the efficacy of the obtained results.

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