Advanced motion control for precision mechatronics: Control, identification, and learning of complex systems
T Oomen - IEEJ Journal of Industry Applications, 2018 - jstage.jst.go.jp
Manufacturing equipment and scientific instruments, including wafer scanners, printers,
microscopes, and medical imaging scanners, require accurate and fast motions. An increase …
microscopes, and medical imaging scanners, require accurate and fast motions. An increase …
Rational basis functions in iterative learning control—with experimental verification on a motion system
Iterative learning control (ILC) approaches often exhibit poor extrapolation properties with
respect to exogenous signals, such as setpoint variations. This brief introduces rational …
respect to exogenous signals, such as setpoint variations. This brief introduces rational …
Batch-to-batch rational feedforward control: from iterative learning to identification approaches, with application to a wafer stage
L Blanken, F Boeren, D Bruijnen… - … /ASME Transactions on …, 2016 - ieeexplore.ieee.org
Feedforward control enables high performance for industrial motion systems that perform
nonrepeating motion tasks. Recently, learning techniques have been proposed that improve …
nonrepeating motion tasks. Recently, learning techniques have been proposed that improve …
Optimality and flexibility in iterative learning control for varying tasks
Abstract Iterative Learning Control (ILC) can significantly enhance the performance of
systems that perform repeating tasks. However, small variations in the performed task may …
systems that perform repeating tasks. However, small variations in the performed task may …
Using iterative learning control with basis functions to compensate medium deformation in a wide-format inkjet printer
The increase of paper size and production speed in wide-format inkjet printing systems is
limited by significant in-plane deformation of the paper during printing. To increase both the …
limited by significant in-plane deformation of the paper during printing. To increase both the …
Sparse iterative learning control with application to a wafer stage: Achieving performance, resource efficiency, and task flexibility
Trial-varying disturbances are a key concern in Iterative Learning Control (ILC) and may
lead to inefficient and expensive implementations and severe performance deterioration …
lead to inefficient and expensive implementations and severe performance deterioration …
Neural-network-based iterative learning control for multiple tasks
D Zhang, Z Wang, T Masayoshi - IEEE transactions on neural …, 2020 - ieeexplore.ieee.org
Iterative learning control (ILC) can synthesize the feedforward control signal for the trajectory
tracking control of a repetitive task, even when the system has strong nonlinear dynamics …
tracking control of a repetitive task, even when the system has strong nonlinear dynamics …
Analysis of the roles of microporosity and BMP-2 on multiple measures of bone regeneration and healing in calcium phosphate scaffolds
SJ Polak, SKL Levengood, MB Wheeler, AJ Maki… - Acta Biomaterialia, 2011 - Elsevier
Osteoinductive agents, such as BMP-2, are known to improve bone formation when
combined with scaffolds. Microporosity (< 20μm) has also been shown to influence bone …
combined with scaffolds. Microporosity (< 20μm) has also been shown to influence bone …
Data-driven iterative inversion-based control: Achieving robustness through nonlinear learning
R de Rozario, T Oomen - Automatica, 2019 - Elsevier
Learning from past data enables substantial performance improvement for systems that
perform repeating tasks. Achieving high accuracy and fast convergence in the presence of …
perform repeating tasks. Achieving high accuracy and fast convergence in the presence of …
Data‐driven multivariable ILC: enhanced performance by eliminating L and Q filters
J Bolder, S Kleinendorst… - International Journal of …, 2018 - Wiley Online Library
Iterative learning control (ILC) algorithms enable high‐performance control design using
only approximate models of the system. To deal with severe modeling errors, a robustness …
only approximate models of the system. To deal with severe modeling errors, a robustness …