Disturbance Rejection and Robustness of Improved Equivalent-Input-Disturbance-Based System

Area of Science:

• Control Systems Engineering
• Robotics
• Automation

Background:

• Existing equivalent-input-disturbance (EID) control methods struggle with unknown disturbances and plant uncertainties.
• Current EID estimators impose constraints between design parameters and uncertainties, limiting performance.
• Insufficient analysis exists on how uncertainties impact control performance and system stability.

Purpose of the Study:

• To present an improved EID approach for handling unknown disturbances and plant uncertainties.
• To develop a new filter for an EID estimator, removing design constraints.
• To analyze the influence of uncertainties on disturbance rejection, reference tracking, and system stability.

Main Methods:

• A novel filter is integrated into the EID estimator to eliminate design constraints.
• The lumped disturbance, combining unknown disturbances and plant uncertainties, is estimated and compensated.
• A sufficient stability criterion is derived, explicitly considering the impact of uncertainties.

Main Results:

• The improved EID estimator successfully compensates for lumped disturbances without design constraints.
• The new filter allows for independent reduction of sensitivity to low-frequency disturbances.
• System analysis confirms that uncertainties affect disturbance rejection, reference tracking, and stability.

Conclusions:

• The proposed improved EID approach effectively handles unknown disturbances and uncertainties.
• The developed method enhances control performance and ensures system stability, even with uncertainties.
• Simulation and experimental results validate the effectiveness of the presented control strategy.