On observer-based controller design for Sugeno systems with unmeasurable premise variables.

Area of Science:

• Control Systems Engineering
• Nonlinear System Analysis
• Fuzzy Logic Systems

Background:

• Takagi-Sugeno (T-S) models are effective for representing nonlinear systems.
• T-S models with unmeasurable premise variables offer broader system representation but increase analytical complexity.
• Observer-based controllers are crucial for estimating system states in feedback control.

Purpose of the Study:

• To design an observer-based controller for continuous-time nonlinear systems described by T-S models with unmeasurable premise variables.
• To simplify the analysis and design complexity associated with these advanced T-S models.
• To ensure exponential convergence of system states for improved control performance.

Main Methods:

• Utilizing a common output model for subsystems within the T-S framework.
• Employing local nonlinear rules to reduce the number of Sugeno model rules.
• Applying fuzzy Lyapunov function analysis for stability guarantees.
• Leveraging Linear Matrix Inequality (LMI) formulation for controller design and analysis.

Main Results:

• A simplified T-S structure that reduces design and analysis complexity.
• Guaranteed exponential convergence of system states.
• Demonstrated effectiveness of the proposed observer-based controller through simulations.

Conclusions:

• The proposed observer-based controller effectively manages nonlinear systems with unmeasurable T-S variables.
• The method offers a computationally tractable approach to complex nonlinear control problems.
• The controller design ensures robust state estimation and system stability.