Zhuyuan Li

Peking University

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Ying Yang

China Three Gorges University

Zhengen Zhao

Nanjing University of Aeronautics and Astronautics

Ruijie Liu

University of Shanghai for Science and Technology

Linlin Li

University of Science and Technology Beijing

Haoran Ma

State Key Laboratory of Turbulence and Complex Systems

Shuyu Ding

Peking University

Steven X. Ding

University of Duisburg-Essen

Jia Wang

Beijing Union University

Haoran Ma

Dalian University of Technology

Xiaolu Chen

Inner Mongolia Electric Power (China)

Cooperative Institutions

State Key Laboratory of Turbulence and Complex Systems

Peking University

Shanghai Jiao Tong University

University of Duisburg-Essen

University of Shanghai for Science and Technology

Huazhong University of Science and Technology

Anhui University of Technology

Northwest Normal University

Nanjing University of Aeronautics and Astronautics

University of Virginia

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Optimal Strictly Stealthy Attack Design on Cyber-Physical Systems: A Data-Driven Approach

IEEE Transactions on Cybernetics (2024)

Zhuyuan Li Zhengen Zhao Steven X. Ding Ying Yang

In this article, an issue of data-driven optimal strictly stealthy attack design for the stochastic linear invariant systems is investigated, with the aim of maximizing the system performance degradation under an energy bounded constraint and bypassing the parity-space-based attack detector. Importantly, the proposed attack policy refrains from the assumption that the system knowledge is known to attackers. A novel strictly stealthy attack sequence (SSAS), coordinating the sensor and actuator signals simultaneously, is proposed with a sufficient and necessary condition for the existence of such an attack presented. Specifically, the SSAS is parameterized as a vector in the null space of a specific matrix which is constructed by a parity matrix and the system Markov parameters. For the purpose of data-driven attack realization, modified subspace identification methods are utilized to achieve an unbiased estimation of the required parameters via the closed-loop data. On this basis, the attack design is formulated as a constrained optimization problem, an explicit solution to which is given to characterize the optimal strictly stealthy attack. Finally, the vulnerability of the cyber-physical systems is analysed from the perspective of the parameter selection for the parity space-based detector. A case study on a three-tank model verifies the efficiency of the proposed approach.

Cyber-physical system

10.1109/tcyb.2024.3413969

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Distributed Fault Detection for Large-Scale Systems Based on Adaptive Approximation

2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS) (2023)

Shuyu Ding Zhuyuan Li Ying Yang

This paper proposes a distributed fault detection scheme for the large-scale system composed of interconnected heterogeneous subsystems. In each subsystem, an adaptive estimator is formed to approximate the unknown interconnection with neighbors using local and neighboring data. Then the exponential convergence of the estimate error is analyzed and the corresponding sufficient conditions are given. Based on the estimated interconnection parameter, a distributed observer based residual generator is constructed in each local diagnoser, which is sensitive to the local and neighboring faults. In addition, location of the actuator and sensor fault can be realized by analyzing detection results of all diagnosers. Finally, case study on a power network verifies the effectiveness of the proposed scheme.

Observer (physics)

10.1109/safeprocess58597.2023.10295595

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Model-Free Fault Detection Based on Performance Residual for Feedback Control Systems

IEEE Transactions on Circuits & Systems II Express Briefs (2022)

Zhuyuan Li Ying Yang Linlin Li Haoran Ma Xiaolu Chen

This brief proposes a control performance-oriented fault detection (PFD) strategy for closed-loop linear time-invariant systems. Firstly, the performance index with the summation of quadratic form over the infinite time interval is investigated in virtue of a data-driven residual-centered closed-loop model, which can be constructed utilizing input and output data instead of system models. Then the adaptive residual generator is presented to update the parameters of the data-driven model in case of system changes caused by anomalies, serving the information of the faulty plant for PFD. Further, the performance residual, which represents the performance degradation, is defined based on the Bellman equation. By embedding the predesigned controller parameters in the performance residual generator, the performance degradation caused by system faults and controller mismatches can be detected. Additionally, the proposed scheme can be applied in various operating points without revising the detector parameters. Finally, a randomized algorithm-aided threshold design is developed to handle unknown input. Case studies on a circuit model are conducted to show the superiority of PFD.

LTI system theory

10.1109/tcsii.2022.3182655

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Citations (6)

Energy Balance Based Attack Detection for Cyber Physical Systems

2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS) (2022)

Zhuyuan Li Ying Yang Zhengen Zhao Ruijie Liu

In this article, the deficiency of a widely-used observer-based attack detection scheme for cyber physical systems (CPS) is analyzed and then a novel dissipativity-based attack detector is proposed. Firstly, the definition of kernel attacks is introduced to capture the stealthy attacks which can not be detected through well-established observer-based techniques. Further, a data-driven design of kernel attacks based on subspace identification methods deploying input and output data is presented. To detect kernel attacks, a dissipativity-based attack detector is formulated in light of energy balance equation, providing a complementary strategy to guarantee reliable detection of attacks. Finally, the validity of the presented approach is demonstrated in a numerical example.

Cyber-physical system

Kernel (algebra)

Observer (physics)

Identification

10.1109/ddcls55054.2022.9858499

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Stable image representation based stability performance monitoring and recovery for feedback control systems

Journal of the Franklin Institute (2022)

Zhuyuan Li Ying Yang Linlin Li Ruijie Liu Jia Wang

Representation

Coprime integers

10.1016/j.jfranklin.2022.08.006

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Citations (2)

Performance-Based Fault-Tolerant Control For Hot Rolling Processes

2022 34th Chinese Control and Decision Conference (CCDC) (2023)

Wenlong Li Zhuyuan Li Ying Yang

In hot rolling processes, equipment fouling, feedstock variations and product changes may cause multiplicative faults, which will considerably affect the system stability and production quality. This paper focuses on performance-based fault-tolerant control (FTC) for multiplicative faults in hot rolling processes. First, the residual-driven fault-tolerant controller is presented through Youla Parameterization, the parameter of which is designed according to the small gain theory to maximize the fault-tolerant margin of the controller. Subsequently, the mechanism formulas of stand and looper are analysed to construct the nonlinear thinkness-looper integrated model, and then the state space model is obtained by linearizing the nonlinear model at the operating point through Taylor Formula. In light of this model, the effectiveness of the proposed FTC strategy is illustrated. It can be observed that the proposed fault-tolerant controller can stabilize the faulty system whereas the nominal controller can not.

10.1109/ccdc58219.2023.10326661

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Data-Driven Passivity Analysis and Fault Detection Using Reinforcement Learning

IEEE Transactions on Circuits and Systems I Regular Papers (2024)

Haoran Ma Zhengen Zhao Zhuyuan Li Ying Yang

Passivity

10.1109/tcsi.2024.3417257

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