Data-Based Distributed Sensor Scheduling for Multiple Linear Systems With H8 Performance Preservation

• 成果类型: Article
• 署名作者: An, Liwei; Yang, Guang-Hong
• 署名单位: Northeastern University - China; Northeastern University - China
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2021.3133181
• 发表日期: 2022
• 页码: 6834-6841
• 关键词: H(8 )performance; distributed optimization; sensor scheduling; wireless sensor networks (WSNs)

摘要

This article investigates the data-based distributed sensor scheduling for a wireless sensor network (WSN), where multiple sensor nodes monitor different linear systems correspondingly. The WSN admits a network topology to formulate a fully distributed sensor scheduling policy, and transmits measured information over a shared wireless channel. Due to the bandwidth limit, at each time only partial sensor nodes can send their measurements to the corresponding remote controller. By introducing a distributed minimum subset extraction mechanism under Q-learning framework, a data-based sensor scheduling algorithm is proposed, which gives an approximate solution to minimizing the H(infinity )performance index of the overall closed-loop system, without requiring the knowledge of system parameters. Also, under persistently exciting condition with sufficiently rich enough disturbances, the algorithm converges to the exact optimal solution. The effectiveness of the proposed algorithm is demonstrated with simulation results.