Robust-optimal control of rotary inverted pendulum control through fuzzy descriptor-based techniques.

Area of Science:

• Control Systems Engineering
• Fuzzy Logic Systems
• Nonlinear Control Theory

Background:

• The Takagi-Sugeno (T-S) fuzzy model is a well-established framework for modeling nonlinear systems.
• Fuzzy descriptor systems extend the T-S model, offering enhanced robustness and flexibility.
• Stability control in uncertain systems remains a significant challenge in control engineering.

Purpose of the Study:

• To develop optimal and robust-optimal controllers for T-S fuzzy descriptor systems.
• To establish conditions for controller design using linear matrix inequalities (LMIs).
• To validate the effectiveness of these controllers in stabilizing complex systems with uncertainties.

Main Methods:

• Development of T-S fuzzy descriptor models.
• Transformation of complex inequalities into linear matrix inequalities (LMIs).
• Design and simulation of optimal and robust-optimal controllers.
• Utilizing the rotary inverted pendulum as a benchmark system.

Main Results:

• The study successfully derived conditions for controller construction via LMIs.
• Controllers based on fuzzy descriptor systems demonstrated practical effectiveness.
• Stable control of the inverted pendulum was achieved despite model uncertainties.

Conclusions:

• Fuzzy descriptor-based controllers offer adaptability and robustness.
• The developed controllers are suitable for complex and uncertain environments.
• This work paves the way for advanced control strategies in challenging applications.