Robust Fault Estimation Design for Discrete-Time Nonlinear Systems via A Modified Fuzzy Fault Estimation Observer

Area of Science:

• Control Systems Engineering
• Nonlinear Dynamics
• Fuzzy Logic Systems

Background:

• Fault estimation is crucial for the reliable operation of nonlinear dynamical systems.
• Existing fault estimation observers often suffer from conservatism, limiting their practical applicability.
• Takagi-Sugeno (T-S) fuzzy models are widely used to represent nonlinear systems.

Purpose of the Study:

• To develop a relaxed fault estimation observer design for nonlinear dynamical plants in the Takagi-Sugeno form.
• To reduce the conservatism inherent in previous fault estimation observer designs.
• To enhance the practical effectiveness of fault estimation techniques for nonlinear systems.

Main Methods:

• A modified fuzzy fault estimation observer is proposed.
• A maximum-priority-based switching law is employed to manage observer design.
• Matrix-valued variables are introduced to exploit plant properties and update system information.
• The design utilizes properties of T-S fuzzy models for nonlinear system representation.

Main Results:

• The proposed observer design achieves less conservatism compared to existing methods.
• The use of a switching law allows for the selection of appropriate design matrices based on system status.
• Abundant plant information is effectively utilized at each time instant, improving estimation.
• Simulation studies demonstrate the effectiveness of the proposed method.

Conclusions:

• The developed fault estimation observer offers a less conservative and more practical solution for nonlinear T-S systems.
• The maximum-priority switching law effectively enhances the performance of fuzzy fault estimation observers.
• The method provides a significant improvement over existing techniques, addressing key practical limitations.