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Related Experiment Video

Updated: Aug 2, 2025

Operation of the Collaborative Composite Manufacturing CCM System
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Iterative learning control for piecewise arc path tracking with validation on a gantry robot manufacturing platform.

Yiyang Chen1, Christopher T Freeman2

  • 1School of Mechanical and Electrical Engineering, Soochow University, Suzhou, 215137, China.

ISA Transactions
|April 14, 2023
PubMed
Summary

Iterative learning control (ILC) enhances manufacturing robots by learning from past trials to improve piecewise arc path tracking accuracy. This new framework offers superior performance compared to existing methods.

Keywords:
Gantry robotIterative learning controlOptimizationPath tracking

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Area of Science:

  • Robotics and Automation
  • Control Systems Engineering
  • Manufacturing Technology

Background:

  • Repetitive manufacturing systems, such as assembly lines, often require end-effectors to follow spatial paths without fixed temporal constraints.
  • Classical feedback control methods struggle with precise trajectory following in such scenarios.
  • Iterative Learning Control (ILC) offers a promising approach by utilizing historical trial data to reduce tracking errors.

Purpose of the Study:

  • To extend the task description of ILC for piecewise arc path tracking.
  • To formulate a more general design framework for spatial ILC.
  • To develop and validate a comprehensive ILC algorithm for this specific application.

Main Methods:

  • Development of a generalized ILC framework tailored for piecewise arc path tracking.
  • Design of a comprehensive ILC algorithm incorporating practical implementation guidelines.
  • Experimental validation using a gantry robot manufacturing testbed.

Main Results:

  • The proposed ILC algorithm effectively handles piecewise arc path tracking tasks.
  • The generalized framework surpasses existing spatial ILC approaches in scope.
  • Experimental results demonstrate superior path tracking accuracy compared to conventional methods.

Conclusions:

  • The developed ILC approach is feasible and efficient for real-world manufacturing applications.
  • This work advances ILC capabilities for complex spatial trajectory following in repetitive tasks.
  • The study confirms the practical benefits of the proposed ILC algorithm in enhancing robotic precision.