Disturbance rejection in fuzzy systems based on two dimensional modified repetitive-control

Area of Science:

• Control Systems Engineering
• Fuzzy Logic Systems
• Robust Control Theory

Background:

• Aperiodic disturbances pose significant challenges to the stability and performance of control systems.
• Existing control strategies often struggle to effectively address complex, time-varying disturbances in fuzzy systems.

Purpose of the Study:

• To design a robust two-dimensional modified repetitive control (2D MRC) system incorporating an improved-equivalent-input-disturbance (IEID) estimator.
• To enhance the stability and disturbance rejection capabilities of fuzzy systems subjected to aperiodic disturbances.

Main Methods:

• Implementation of an IEID-estimator within the 2D MRC framework to estimate and compensate for all disturbance types.
• Development of a 2D MRC system capable of independent continuous control and discrete learning behaviors.
• Derivation of robust stability conditions using linear-matrix-inequalities (LMIs) to determine observer and controller gains.

Main Results:

• The proposed IEID-based 2D MRC effectively estimates and compensates for aperiodic disturbances, ensuring robust stability.
• The control system demonstrates independent continuous control and discrete learning functionalities.
• Simulation results validate the efficacy of the proposed control technique across three numerical examples.

Conclusions:

• The IEID-based robust 2D MRC offers a powerful solution for controlling fuzzy systems with aperiodic disturbances.
• The derived LMI conditions provide a systematic approach to designing stable and robust controllers.
• The proposed method significantly improves system performance and robustness in the presence of uncertainties.