Hybrid Nash Equilibrium Seeking Under Partial-Decision Information: An Adaptive Dynamic Event-Triggered Approach

• 成果类型: Article
• 署名作者: Xu, Wenying; Wang, Zidong; Hu, Guoqiang; Kurths, Jurgen
• 署名单位: Southeast University - China; Brunel University; Nanyang Technological University; Potsdam Institut fur Klimafolgenforschung; Lobachevsky State University of Nizhni Novgorod
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3226142
• 发表日期: 2023
• 页码: 5862-5876
• 关键词: adaptive control; distributed Nash equilibrium (NE) seeking; Distributed network; event-triggered communication (ETC); partial-decision information

摘要

This article is concerned with the hybridNash equilibrium (NE) seeking problem over a network in a partial-decision information scenario. Each agent has access to both its own cost function and local decision information of its neighbors. First, an adaptive gradient-based algorithm is constructed in a fully distributed manner with the guaranteed convergence to the NE, where the network communication is required. Second, in order to save communication cost, a novel event-triggered scheme, namely, edge-based adaptive dynamic event-triggered (E-ADET) scheme, is proposed with online-tuned triggering parameter and threshold, and such a scheme is proven to be fully distributed and free of Zeno behavior. Then, a hybrid NE seeking algorithm, which is also fully distributed, is constructed under the E-ADET scheme. By means of the Lipschitz continuity and the strong monotonicity of the pseudogradient mapping, we show the convergence of the proposed algorithms to the NE. Compared with the existing distributed algorithms, our algorithms remove the requirement on global information, thereby exhibiting the merits of both flexibility and scalability. Finally, two examples are provided to validate the proposed NE seeking methods.