Synthesis of robust multivariable iterative learning controllers with application to a wafer stage motion system

D. de Roover; Okko H. Bosgra

doi:10.1080/002071700405923

January 1, 2000International Journal of Control

Synthesis of robust multivariable iterative learning controllers with application to a wafer stage motion system

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Key Points

To synthesize robust multivariable iterative learning controllers that systematically enhance transient tracking performance in repetitive wafer stage positioning systems.
Formulated multivariable iterative learning control within an H-infinity robust control framework to move beyond empirical heuristics.
Synthesized learning algorithms tailored for multivariable interactions and disturbances in precision wafer stage motion hardware.
Derived a non-heuristic, robust iterative learning control synthesis framework capable of managing multivariable system dynamics.
Demonstrated qualitative reduction in transient tracking errors across repeated cycles without compromising system stability under model uncertainty.

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Implication

Control design study demonstrates robust multivariable iterative learning control for wafer stage motion systems, indicating improved transient precision in repetitive industrial positioning.

Abstract

Iterative Learning Control (ILC) is a powerful control concept that iteratively improves the transient behaviour of processes that are repetitive in nature. Although most of the published ILC schemes are heuristic in nature, some initial research has been performed on the formulation of the ILC problem in the H

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Roover et al. (2000) studied this question.

synapsesocial.com/papers/6ab70db6f2724f881dc8b2a3 https://doi.org/10.1080/002071700405923

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Synthesis of robust multivariable iterative learning controllers with application to a wafer stage motion system

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Synthesis of robust multivariable iterative learning controllers with application to a wafer stage motion system

Key Points

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Implication

Abstract

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