Event-Triggered H∞ Filtering for T-S Fuzzy-Model-Based Nonlinear Networked Systems With Multisensors Against DoS
IEEE Transactions on Cybernetics
|November 5, 2020
Summary
This study introduces resilient H∞ filtering for nonlinear networked systems, enhancing data transmission security and reducing data rates using an event-triggered mechanism. It addresses denial-of-service attacks, ensuring system stability.
Area of Science:
- Control Systems Engineering
- Networked Systems
- Fuzzy Logic Systems
Background:
- Multisensor nonlinear systems face challenges in data transmission and security over networks.
- Denial-of-Service (DoS) attacks pose significant threats to networked system reliability.
Purpose of the Study:
- To develop a resilient H∞ filter for Takagi-Sugeno fuzzy-model-based nonlinear networked systems.
- To enhance data fusion and mitigate the impact of DoS attacks.
Main Methods:
- A weighted fusion approach for multisensor data before network transmission.
- A novel event-triggered mechanism to reduce data release rate and prevent abnormal data.
- Employing a switching model for filtering error systems to counter DoS attacks.
Main Results:
- The proposed event-triggered mechanism effectively reduces data transmission rates.
- Sufficient conditions for exponential stability of the filtering error system under DoS attacks were derived.
- Simulation results validated the theoretical analysis and design method's effectiveness.
Conclusions:
- The developed resilient H∞ filtering approach is effective for nonlinear networked systems.
- The event-triggered mechanism and DoS attack handling improve system robustness and efficiency.
- The study provides a robust framework for secure and stable networked system operation.
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