Adaptive Disturbance Rejection Motion Control of Direct-Drive Systems with Adjustable Damping Ratio Based on...

Area of Science:

• Robotics and Control Systems
• Mechatronics
• Applied Physics

Background:

• Direct-drive servo systems are crucial for biomimetic robotics but suffer from performance degradation due to uncertainties and disturbances.
• Existing control methods often struggle with model parameter uncertainties and external disturbances, limiting precision.
• Iron-core permanent magnet linear synchronous motors (PMLSMs) are common platforms requiring robust control strategies.

Purpose of the Study:

• To develop an adaptive disturbance rejection Zeta-backstepping control scheme with adjustable damping ratios for enhanced robustness and precision in direct-drive servo systems.
• To address model parameter uncertainties and unmodeled dynamics in PMLSMs.
• To provide a flexible control approach for achieving desired dynamic performance in bionic applications.

Main Methods:

• Development of a dynamic model for an iron-core PMLSM, including compensation for friction and cogging forces.
• Implementation of an indirect parameter adaptation strategy using a recursive least squares algorithm for robust parameter convergence based on system states.
• Construction of an integral sliding mode observer (ISMO) for finite-time estimation and compensation of residual uncertainties.
• Design of a Zeta-backstepping controller with parameterized control laws for adjustable damping ratios.
• Validation of system stability and bounded tracking performance using second-order Lyapunov function analysis.

Main Results:

• The proposed adaptive control scheme significantly improves tracking accuracy and disturbance suppression in PMLSMs.
• The controller successfully achieves adjustable damping ratio characteristics, offering performance flexibility.
• Robust parameter convergence was achieved through the indirect adaptation strategy, even with system state-based updates.
• The integral sliding mode observer effectively estimated and compensated for system uncertainties in finite time.
• Experimental validation on a PMLSM platform confirmed the theoretical predictions and practical effectiveness.

Conclusions:

• The adaptive disturbance rejection Zeta-backstepping control scheme offers a robust and precise solution for direct-drive servo systems.
• The adjustable damping ratio feature provides enhanced flexibility for optimizing dynamic performance in various applications.
• The developed control strategy demonstrates significant potential for advancing precision control in biomimetic robotics and other bionic systems.
• The combination of parameter adaptation and integral sliding mode observation effectively handles system uncertainties and disturbances.