Real-Time Fault Detection Approach for Nonlinear Systems and its Asynchronous T-S Fuzzy Observer-Based Implementation

Area of Science:

• Control Systems Engineering
• Nonlinear System Analysis
• Fault Detection and Diagnosis

Background:

• Real-time fault detection (FD) is crucial for the safety and reliability of nonlinear dynamic systems.
• External disturbances pose significant challenges to the accuracy and effectiveness of traditional FD methods.
• Observer-based approaches offer a promising framework for detecting faults in complex systems.

Purpose of the Study:

• To develop a real-time observer-based fault detection (FD) approach for general nonlinear systems.
• To design an L∞/L2 type nonlinear observer-based FD system capable of handling external disturbances.
• To integrate Takagi-Sugeno (T-S) fuzzy dynamic modeling for enhanced FD system design.

Main Methods:

• Definition and design conditions for L∞/L2 nonlinear observer-based FD systems.
• Application of Takagi-Sugeno (T-S) fuzzy dynamic modeling for integrated FD system design.
• Development of the fuzzy observer-based FD approach using piecewise Lyapunov functions.

Main Results:

• An analytical framework for real-time nonlinear FD systems was established.
• The proposed T-S fuzzy observer-based FD approach effectively handles nonsynchronous premise variables.
• The method demonstrated efficiency in a case study on a laboratory three-tank system.

Conclusions:

• The proposed observer-based fault detection approach provides a robust solution for nonlinear systems.
• The integration of T-S fuzzy logic enhances the performance and applicability of FD systems.
• The developed method is effective in real-time fault detection even under external disturbances.