Aug 2026· ISA transactions· 0 citations· 35 references
Medicine
TL;DR
Simulations on a steam temperature cascade control system validate the effectiveness of the proposed method, demonstrating 20% faster convergence and a 67% reduction in oscillations compared with a conventional method while maintaining stability and security under hybrid attacks.
Abstract
This paper presents a resilient control framework for networked cascade systems (NCCSs) subject to transmission delays and hybrid cyber-attacks involving false data injection (FDI) and Denial-of-Service (DoS) attacks. The hybrid attack model is defined by the asynchronous operation of these two threats: DoS attacks disrupt data availability by blocking the communication channel, while FDI attacks compromise data integrity by injecting false signals during the DoS dormant periods. Accordingly, an event-triggered mechanism and a neural network-based estimator are co-designed to reduce the network transmission burden and identify and compensate for unstructured FDI attack signals. The closed-loop system is modeled as a switched system, and sufficient stability conditions under hybrid attacks are derived through a Lyapunov-based neural network approach to facilitate the design of an H∞ controller with guaranteed robust performance. Simulations on a steam temperature cascade control system validate the effectiveness of the proposed method, demonstrating 20% faster convergence and a 67% reduction in oscillations compared with a conventional method while maintaining stability and security under hybrid attacks.
A novel adaptive discrete event-triggered communication scheme (ADETCS) is proposed that effectively counteracts coexisting attacks and faults while significantly reducing resource consumption.
Li Zhao, Wei Li, Nani Han· Italian National Conference...· 0 citations
Cyber-physical systems (CPSs) are widely used in safety-critical applications, where both control reliability and communication efficiency are essential. However, open networks make CPSs vulnerable to false data injection (FDI) attacks, which threaten system stability. Existing event-triggered control methods often fail to simultaneously ensure attack resilience, stability, and $H_\infty$ performance. This paper addresses the secure control problem of CPSs under FDI attacks by proposing an observer-based dynamic event-triggered control framework. To counteract the adversarial disturbances, a novel attack-resilient observer is designed to simultaneously estimate both the system states and the injected attack signals, enabling the synthesis of a secure observer-based controller. An advanced dynamic event-triggered mechanism (DETM) is developed by incorporating an internal dynamic variable, which adaptively adjusts triggering thresholds to significantly reduce communication frequency while avoiding Zeno behavior. Through Lyapunov-Razumikhin analysis, the closed-loop system is proven to achieve asymptotic stability and guaranteed $H_\infty$ performance, ensuring robustness against bounded FDI attacks. Theoretical results are validated via numerical simulations, demonstrating the effectiveness of the proposed method in mitigating attack impacts and conserving network resources.
Lei Liu, Ruonan Ren, Baoling Miao· IEEE Transactions on Industr...· 0 citations
This article investigates the asynchronous mixed $H_{\infty } $ and passive control for discrete-time switched systems subject to denial-of-service (DoS) attacks and communication resource constraints. In order to alleviate the communication pressure, an event-triggered mechanism (ETM) is adopted. However, due to the introduction of ETM, the asynchronous phenomenon may occur between the subsystem and controller. In addition, DoS attacks can have adverse effects on system performance by interfering with communication channels. To address the above issues, a weighted mixed $H_{\infty } $ and passivity performance criterion is adopted to balance disturbance attenuation and energy dissipation. On this basis, the Lyapunov function method is used to design the average dwell time (ADT) switching signal, ensuring that the asynchronous switched system is globally uniformly asymptotically stable (GUAS). Meanwhile, the design strategy of the controller is presented in the form of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed method is demonstrated through a practical example.
Liang Zhang, Jing Liang, N. Zhao et al.· IEEE Transactions on Cyberne...· 1 citation
In this work, an adaptive fixed-time dynamic triggered control issue for interconnected power systems under Denial-of-Service (DoS) attacks is investigated. Such attacks would impede the transmission of sensor signals in interconnected power systems, precipitating a severely unstable power supply or even paralysis. To effectively confront this challenge, an adaptive switching neural network state observer is designed. The observer can maintain the output of the observation state under both attack conditions and normal conditions, thereby compensating for the adverse effects of DoS attacks on interconnected power systems. Meanwhile, a nonlinear fixed-time filter is constructed, which not only obviates the complexity explosion issue but also enhances the convergence capability of interconnected power systems. Moreover, a dual dynamic parameter threshold Event-Triggered Mechanism (ETM) is developed. Influenced by multiple dynamic parameters, this mechanism achieves a more precise control of triggered conditions, drastically conserving the communication resources of the interconnected power systems and preventing the occurrence of Zeno behavior. Ultimately, the effectiveness of the proposed methods is demonstrated by the simulation results.
This paper investigates the problem of event-triggered secure regulation for high-order fully actuated (HOFA) systems subject to stochastic denial-of-service (DoS) attacks. Through a suitable state transformation, the original HOFA plant is recast into an error-state representation. A dual-dynamic event-triggered control (DETC) law is devised, which operates solely during DoS sleep intervals. By employing Lyapunov-based arguments, sufficient conditions are derived to ensure the practical stability of the closed-loop system for both attack and sleep phases. Moreover, a strictly positive lower bound on the minimum inter-event interval is established, thereby ruling out Zeno phenomena. Numerical experiments confirm the effectiveness of the proposed approach.
The linear optimal output regulation problem (LOORP) of discrete-time (DT) cyber-physical systems (CPSs) under false data injection attacks (FDIAs) is investigated in this article. First, the LOORP under FDIAs is reduced to a static optimization problem and a dynamic minimax problem, and the corresponding model-based schemes are provided to solve these two problems. Afterward, a hybrid iteration (HI)-based Q-learning scheme is proposed to solve the two issues online. This scheme requires neither exact system dynamics information nor an initially stabilizing control gain, which also achieves a fast iteration speed. Finally, a discretized $LCL$ -coupled inverter-based distributed generation system is presented to demonstrate the performance of the proposed scheme.
Zheng Huang, Jiacheng Wu, Ju H. Park et al.· IEEE Transactions on Cyberne...· 1 citation
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