Finite-time extended dissipative control for fuzzy systems with nonlinear perturbations via sampled-data and...

Area of Science:

• Control Systems Engineering
• Fuzzy Logic Systems
• Nonlinear Systems

Background:

• Addressing control challenges in Takagi-Sugeno (T-S) fuzzy systems with time-varying delays and nonlinear perturbations.
• The need for robust control strategies that account for sampled-data and quantization effects.

Purpose of the Study:

• To propose a novel finite-time extended dissipative control method for T-S fuzzy time-varying delay systems.
• To develop a sampled-data and quantized controller ensuring finite-time boundedness and mixed extended dissipativity.

Main Methods:

• Introduction of a new definition for finite-time bounded mixed extended dissipativity in fuzzy systems.
• Utilization of Lyapunov-Krasovskii functionals (LKF) and Peng-Parks integral inequality.
• Formulation of sufficient conditions using linear matrix inequalities (LMIs).

Main Results:

• Development of a less conservative set of conditions for system stability compared to existing methods.
• Design of a controller integrating input delay and dynamic quantizer for sampled-data systems.
• Demonstration of the controller's effectiveness in achieving finite-time bounded mixed extended dissipativity.

Conclusions:

• The proposed control strategy effectively guarantees finite-time bounded mixed extended dissipativity for the considered fuzzy systems.
• The LMI-based conditions offer improved performance and reduced conservatism.
• Numerical and practical examples validate the feasibility and effectiveness of the developed control approach.