A time-varying Q-filter design for iterative learning control

Douglas A. Bristow; Andrew Alleyne; Marina Tharayil

doi:10.1109/ACC.2007.4282553

A time-varying Q-filter design for iterative learning control

Douglas A. Bristow
, Andrew Alleyne
, Marina Tharayil

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Linear time-invariant (LTI) lowpass Q-filters are often employed in iterative learning control (ILC) algorithms to provide robustness to model uncertainty at the expense of learning bandwidth. Whenever high frequency control is necessary, such as motion commands with rapid changes, precision tracking requirements may not be met. In this work, we examine the use of linear time-varying (LTV) Q-filters to create a time-varying learning bandwidth. Single-input single-output LTI plants with repeating disturbances are considered. Stability analysis for the LTV Q-filter learning algorithm is developed and an LTV Q-filter design procedure is presented incorporating time-frequency analysis of the tracking error and optimization. This procedure is used to design an LTV Q-filter for a microscale robotic deposition manufacturing system. Simulation and experimental results are provided, which demonstrate that the designed LTV Q-filter results in faster convergence and lower converged error than the best LTI Q-filter.

Original language	English (US)
Title of host publication	Proceedings of the 2007 American Control Conference, ACC
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5503-5508
Number of pages	6
ISBN (Print)	1424409888, 9781424409884
DOIs	https://doi.org/10.1109/ACC.2007.4282553
State	Published - 2007
Externally published	Yes
Event	2007 American Control Conference, ACC - New York, NY, United States Duration: Jul 9 2007 → Jul 13 2007

Publication series

Name	Proceedings of the American Control Conference
ISSN (Print)	0743-1619

Other

Other	2007 American Control Conference, ACC
Country/Territory	United States
City	New York, NY
Period	7/9/07 → 7/13/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

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10.1109/ACC.2007.4282553

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A time-varying Q-filter design for iterative learning control. / Bristow, Douglas A.; Alleyne, Andrew; Tharayil, Marina.
Proceedings of the 2007 American Control Conference, ACC. Institute of Electrical and Electronics Engineers Inc., 2007. p. 5503-5508 4282553 (Proceedings of the American Control Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Bristow, DA, Alleyne, A & Tharayil, M 2007, A time-varying Q-filter design for iterative learning control. in Proceedings of the 2007 American Control Conference, ACC., 4282553, Proceedings of the American Control Conference, Institute of Electrical and Electronics Engineers Inc., pp. 5503-5508, 2007 American Control Conference, ACC, New York, NY, United States, 7/9/07. https://doi.org/10.1109/ACC.2007.4282553

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abstract = "Linear time-invariant (LTI) lowpass Q-filters are often employed in iterative learning control (ILC) algorithms to provide robustness to model uncertainty at the expense of learning bandwidth. Whenever high frequency control is necessary, such as motion commands with rapid changes, precision tracking requirements may not be met. In this work, we examine the use of linear time-varying (LTV) Q-filters to create a time-varying learning bandwidth. Single-input single-output LTI plants with repeating disturbances are considered. Stability analysis for the LTV Q-filter learning algorithm is developed and an LTV Q-filter design procedure is presented incorporating time-frequency analysis of the tracking error and optimization. This procedure is used to design an LTV Q-filter for a microscale robotic deposition manufacturing system. Simulation and experimental results are provided, which demonstrate that the designed LTV Q-filter results in faster convergence and lower converged error than the best LTI Q-filter.",

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AB - Linear time-invariant (LTI) lowpass Q-filters are often employed in iterative learning control (ILC) algorithms to provide robustness to model uncertainty at the expense of learning bandwidth. Whenever high frequency control is necessary, such as motion commands with rapid changes, precision tracking requirements may not be met. In this work, we examine the use of linear time-varying (LTV) Q-filters to create a time-varying learning bandwidth. Single-input single-output LTI plants with repeating disturbances are considered. Stability analysis for the LTV Q-filter learning algorithm is developed and an LTV Q-filter design procedure is presented incorporating time-frequency analysis of the tracking error and optimization. This procedure is used to design an LTV Q-filter for a microscale robotic deposition manufacturing system. Simulation and experimental results are provided, which demonstrate that the designed LTV Q-filter results in faster convergence and lower converged error than the best LTI Q-filter.

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ER -

A time-varying Q-filter design for iterative learning control

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