Event-triggered fault detection for discrete-time T-S fuzzy systems
Xiao-Lei Wang1, Guang-Hong Yang2
1College of Information Science and Engineering, Northeastern University, Shenyang, 110819, PR China.
ISA Transactions
|March 6, 2018
Summary
This study introduces a piecewise fuzzy diagnostic observer for discrete-time T-S fuzzy systems with an event-triggered (ET) mechanism. The method enhances fault detection (FD) performance using the scaled small gain theorem and Lyapunov-Krasovskii functionals.
Area of Science:
- Control Systems Engineering
- Fuzzy Logic Systems
- Fault Detection and Diagnosis
Background:
- Event-triggered (ET) communication mechanisms can cause premise variable mismatches in fuzzy diagnostic observers.
- Accurate fault detection (FD) is crucial for the reliability of discrete-time Takagi-Sugeno (T-S) fuzzy systems.
Purpose of the Study:
- To design a piecewise fuzzy diagnostic observer for discrete-time T-S fuzzy systems operating under an ET communication mechanism.
- To address premise variable mismatches caused by the ET mechanism for improved fault detection.
- To optimize fault detection performance using advanced control theories.
Main Methods:
- A partition method-based piecewise fuzzy diagnostic observer is designed.
- A two-term approximation approach is used for time-varying delay approximation.
- The scaled small gain (SSG) theorem and a piecewise Lyapunov-Krasovskii functional are employed.
- An input-output form transformation of the augmented system is utilized.
Main Results:
- The design conditions for the piecewise fuzzy diagnostic observer are derived.
- The L∞/L2 and L∞ fault detection (FD) scheme is applied to enhance FD performance.
- Simulation examples demonstrate the effectiveness of the proposed observer design.
Conclusions:
- The proposed piecewise fuzzy diagnostic observer effectively handles premise variable mismatches in ET systems.
- The developed method achieves optimized fault detection performance.
- The approach is validated through simulation, confirming its practical applicability.
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