Iterative learning control for piecewise arc path tracking with validation on a gantry robot manufacturing platform
Iterative learning control for piecewise arc path tracking with validation on a gantry robot manufacturing platform
The piecewise arc path tracking problem is a common feature of manufacturing systems operating in a repetitive mode, e.g. assembly production lines. Here, the system end-effector must follow a spatial path without any specific temporal tracking constraints, which makes the temporal profile not fixed a priori. The technique of iterative learning control (ILC) is well-suited to handle this problem, since compared to classical feedback control methods, ILC is capable of learning from previous trial information to minimize the tracking error over repeated trials. This paper extends the ILC task description to address piecewise arc path tracking tasks, and further formulates a more general design framework than existing spatial ILC approaches. A comprehensive ILC algorithm is designed to handle this class of piecewise arc path tracking problems, and practical implementation instructions are provided. Validation is conducted on a gantry robot manufacturing testbed to confirm its feasibility and efficiency in practice with a comparison to existing methods showing its higher path tracking accuracy.
Gantry robot, Iterative learning control, Optimization, Path tracking
650-659
Chen, Yiyang
2633396c-fcb8-4b50-8104-3d0da5d734cc
Freeman, Christopher
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
August 2023
Chen, Yiyang
2633396c-fcb8-4b50-8104-3d0da5d734cc
Freeman, Christopher
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Chen, Yiyang and Freeman, Christopher
(2023)
Iterative learning control for piecewise arc path tracking with validation on a gantry robot manufacturing platform.
ISA Transactions, 139, .
(doi:10.1016/j.isatra.2023.03.046).
Abstract
The piecewise arc path tracking problem is a common feature of manufacturing systems operating in a repetitive mode, e.g. assembly production lines. Here, the system end-effector must follow a spatial path without any specific temporal tracking constraints, which makes the temporal profile not fixed a priori. The technique of iterative learning control (ILC) is well-suited to handle this problem, since compared to classical feedback control methods, ILC is capable of learning from previous trial information to minimize the tracking error over repeated trials. This paper extends the ILC task description to address piecewise arc path tracking tasks, and further formulates a more general design framework than existing spatial ILC approaches. A comprehensive ILC algorithm is designed to handle this class of piecewise arc path tracking problems, and practical implementation instructions are provided. Validation is conducted on a gantry robot manufacturing testbed to confirm its feasibility and efficiency in practice with a comparison to existing methods showing its higher path tracking accuracy.
Text
Iterative Learning Control for Piecewise Arc Path Tracking with Validation on A Gantry Robot Manufacturing Platform
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Restricted to Repository staff only until 31 March 2025.
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Accepted/In Press date: 31 March 2023
e-pub ahead of print date: 5 April 2023
Published date: August 2023
Additional Information:
Funding Information:
This work was funded by National Natural Science Foundation of China under Grant 62103293 , Natural Science Foundation of Jiangsu Province under Grant BK20210709 , Suzhou Municipal Science and Technology Bureau under Grant SYG202138 , and Entrepreneurship and Innovation Plan of Jiangsu Province under Grant JSSCBS20210641 .
Publisher Copyright:
© 2023 ISA
Keywords:
Gantry robot, Iterative learning control, Optimization, Path tracking
Identifiers
Local EPrints ID: 476801
URI: http://eprints.soton.ac.uk/id/eprint/476801
ISSN: 0019-0578
PURE UUID: f68aa6e1-b9a5-4a5a-8fa7-7acae184d4a9
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Date deposited: 16 May 2023 16:53
Last modified: 17 Mar 2024 01:37
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Contributors
Author:
Yiyang Chen
Author:
Christopher Freeman
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