Co-Design of Data-Driven Attack Observer and Resilient Controller for Unknown NCSs Under Hybrid Attacks

• 成果类型: Article
• 署名作者: Hu, Songlin; Liang, Jiaxin; Chen, Xiaoli; Zhang, Jin; Xie, Xiangpeng
• 署名单位: Nanjing University of Posts & Telecommunications; Nanjing University of Posts & Telecommunications; Nanjing University of Posts & Telecommunications; Nanjing University of Finance & Economics; Shanghai University; Nanjing University of Posts & Telecommunications
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2025.3632690
• 发表日期: 2026
• 关键词: NETWORKED CONTROL-SYSTEMS; FDI ATTACKS; state

摘要

This article proposes a data-driven estimation and control co-design method for a class of unknown linear network control systems (NCSs) under denial-of-service (DoS) and false data injection (FDI) attacks simultaneously. First, a new piecewise observer is designed to provide the real-time estimates of the unavailable system state and the unknown FDI attack signal in the presence of DoS attacks. Under the assumption that the system matrices of the considered NCSs are known in advance, model-based exponential stability criteria are established by utilizing attack-dependent time-varying Lyapunov function method. Second, to extend the obtained model-based stability criteria under hybrid attacks to data-driven paradigm, a new technical lemma, called data-driven system representation under DoS attacks, is proposed. Based on this technical lemma, data-driven stability conditions of unknown NCSs under hybrid attacks are derived in terms of data-based linear matrix inequalities. Third, a security controller design method is proposed within the framework of data-driven methodology. Finally, the effectiveness of the proposed data-based security control strategy for unknown NCSs under hybrid attacks is verified through numerical simulation.