Secure Finite-Time Filtering for Switched Fuzzy Systems with Scaling Attacks and Stochastic Sensor Faults
Research on Secure Finite-Time Filter Design for Switched Fuzzy Systems
Academic Background
In modern control systems, switched systems and fuzzy systems have garnered significant attention due to their effectiveness in handling complex nonlinear dynamics. However, with the proliferation of networked systems, these systems face threats from sensor faults and cyberattacks (e.g., scaling attacks). Sensor faults can degrade system performance, while scaling attacks disrupt system stability by modifying the scaling properties of transmitted data. Therefore, designing a robust filter capable of simultaneously addressing sensor faults and cyberattacks has become a critical research topic.
This paper aims to propose a secure finite-time mixed H∞ and passivity (MHAP) filter design method for discrete-time switched fuzzy systems. The method ensures system robustness within a finite time while effectively mitigating stochastic sensor faults and scaling attacks.
Source of the Paper
This paper is co-authored by Murugesan Sathishkumar, Maya Joby, Yong-Ki Ma, Selvaraj Marshal Anthoni, and Srimanta Santra. The authors are affiliated with SRM Institute of Science and Technology (India), SCMS Cochin School of Business (India), Kongju National University (South Korea), Anna University Regional Campus (India), and the Massachusetts Institute of Technology (USA), respectively. The paper was accepted by the journal Nonlinear Dynamics on February 23, 2025, and published in the same year with the DOI 10.1007/s11071-025-11042-1.
Research Process
1. System Modeling and Problem Description
The study begins by modeling the switched fuzzy system, considering the impact of sensor faults and scaling attacks. Sensor faults are modeled as random variables, while scaling attacks are described using Bernoulli random variables. The research objective is to design a filter that ensures system robustness within a finite time and satisfies the mixed H∞ and passivity performance index.
2. Lyapunov Function Design
To analyze system stability, the study employs the Lyapunov functional approach. By designing an appropriate Lyapunov function and integrating finite-time theory, the study derives a new set of sufficient conditions expressed as linear matrix inequalities (LMIs).
3. Numerical Simulation and Validation
To validate the effectiveness of the proposed method, the study conducts two numerical simulation experiments based on the continuous-time single-link robot arm model and the tunnel diode circuit system. The simulation results demonstrate that the designed filter can effectively handle sensor faults and scaling attacks within a finite time while meeting the predefined performance criteria.
Main Results
1. Finite-Time Boundedness Analysis
Using the Lyapunov function and finite-time theory, the study successfully derives a set of LMI conditions that ensure robust stochastic finite-time boundedness (RSFTB) for the switched fuzzy system. These conditions account for the randomness of sensor faults and model scaling attacks.
2. Mixed H∞ and Passivity Performance Analysis
The study further proves that the designed filter satisfies the mixed H∞ and passivity performance index. By introducing LMI conditions, the study ensures system stability within a finite time and effectively reduces the impact of external disturbances on system performance.
3. Numerical Simulation Validation
The simulation results show that the proposed filter performs excellently in handling sensor faults and scaling attacks. Specifically, in the single-link robot arm model and tunnel diode circuit system, the filter effectively estimates the system states and maintains system stability.
Conclusion and Significance
This paper proposes a secure finite-time mixed H∞ and passivity filter design method for switched fuzzy systems. The method not only effectively addresses stochastic sensor faults and scaling attacks but also ensures system robustness within a finite time. The innovation of the research lies in integrating finite-time theory with the Lyapunov function to derive a new set of LMI conditions, providing new theoretical support for the secure control of switched fuzzy systems.
Research Highlights
- Handling Complex Nonlinear Systems: The paper proposes an effective filter design method for switched fuzzy systems, which are complex nonlinear systems.
- Addressing Multiple Threats: The study simultaneously considers sensor faults and scaling attacks, expanding the application scenarios of the filter.
- Application of Finite-Time Theory: By applying finite-time theory, the study ensures system stability within a finite time, offering significant practical value.
- Numerical Simulation Validation: The simulation experiments validate the effectiveness of the proposed method, further enhancing the credibility of the theory.
Other Valuable Information
This research provides new insights into the secure design of networked control systems, particularly in addressing sensor faults and cyberattacks, with broad application prospects. Future research can further explore the applicability of this method in other complex systems and consider more types of cyberattacks and sensor fault models.