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Related Experiment Video

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Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

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Published on: April 4, 2017

Sliding-mode repetitive learning control with integral sliding-mode perturbation compensation.

Yu-Sheng Lu¹, Xuan-Wen Wang

¹Department of Mechatronic Technology, National Taiwan Normal University, Taipei 106, Taiwan. luys@ntnu.edu.tw

ISA Transactions

|December 17, 2008

Summary

A novel sliding-mode repetitive learning control (SMRLC) scheme integrates an integral sliding-mode perturbation observer (ISMPO) for superior repetitive tracking. This robust control method ensures minimal error and fast learning convergence in repetitive tasks.

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Area of Science:

Control Systems Engineering
Robotics
Automation

Background:

Repetitive tracking control is crucial for systems performing similar tasks multiple times.
Existing methods may struggle with disturbances and initial learning phases.
Robustness and fast convergence are key challenges in repetitive control.

Purpose of the Study:

To propose a novel sliding-mode repetitive learning control (SMRLC) scheme.
To enhance tracking performance and robustness in repetitive tasks.
To achieve fast convergence of the learning process.

Main Methods:

Integration of pole-placement feedback control for error dynamics.
Implementation of an integral sliding-mode perturbation observer (ISMPO) for robust feedback compensation.
Development of a feedforward learning component updated via a switching signal for error compensation.

Main Results:

The proposed SMRLC scheme with ISMPO demonstrated excellent tracking performance.
ISMPO-based compensation ensured small tracking errors and robustness to disturbances.
The feedforward learning component achieved fast convergence across trials.

Conclusions:

The developed SMRLC scheme with ISMPO is a feasible and effective approach for repetitive tracking control.
The combination of robust feedback and feedforward learning significantly improves system performance.
This control strategy offers enhanced insensitivity to aperiodic disturbances.