Advances in iterative learning control: A recent five-year literature review

Area of Science:

• Control Engineering
• Automation Systems
• Systems Science

Background:

• Iterative learning control (ILC) is a specialized control strategy for finite-length, repeatable batch processes.
• The field has matured over four decades but lacks recent comprehensive reviews, hindering a holistic understanding of progress.

Purpose of the Study:

• To provide a systematic literature review of recent key developments in Iterative Learning Control (ILC).
• To identify current trends and future research directions in ILC.
• To offer a holistic understanding of the state-of-the-art in ILC.

Main Methods:

• A comprehensive literature review was conducted, focusing on recent advancements.
• Key developments were analyzed across five essential dimensions: system dynamics, signal acquisition, reference trajectory, algorithm design, and implementations/applications.
• Major advancements and contributions were summarized, followed by critical discussions and forward-looking perspectives.

Main Results:

• Significant advancements in ILC have been observed across system dynamics, signal processing, algorithm design, and practical applications.
• The review highlights progress in handling complex system dynamics and improving algorithm robustness and convergence.
• Emerging trends include advanced implementations and broader application domains for ILC.

Conclusions:

• This review provides a consolidated overview of recent ILC progress, aiding researchers and practitioners.
• It identifies key research trends and potential future directions for both theoretical and applied ILC development.
• The findings aim to stimulate further innovation and application of ILC in various engineering fields.