Point-to-point iterative learning control with quantised input signal and actuator faults
Point-to-point iterative learning control with quantised input signal and actuator faults
This paper applies iterative learning control to point-to-point tracking problems with a general networked structure. The data is quantised and transmitted through restricted communication channels from the controller to the actuator. Combining a logarithmic quantizer with an encoding and decoding mechanism to quantise the input signals reduces the influence of the quantisation error. New design algorithms are developed with conditions for convergence of the tracking error and an extension to fault-tolerant performance under actuator failures. A numerical-based case study demonstrates the application of the new designs, which includes a comparison with another ILC law and the relative merits of the encoding and decoding schemes.
Iterative learning control, encoding-decoding mechanism, fault-tolerant, optimal design, quantised input signal
Huang, Yande
df62b99c-9396-449c-8470-323ec62292f4
Tao, Hongfeng
565ef1a8-eb2c-4139-bdd9-ebd5baf4eebe
Chen, Yiyang
bbcd67b6-eb72-4897-861e-a2bb330ca226
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72
Paszke, Wojciech
81c57e06-5f8c-4905-9922-66090aa2e20c
Huang, Yande
df62b99c-9396-449c-8470-323ec62292f4
Tao, Hongfeng
565ef1a8-eb2c-4139-bdd9-ebd5baf4eebe
Chen, Yiyang
bbcd67b6-eb72-4897-861e-a2bb330ca226
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72
Paszke, Wojciech
81c57e06-5f8c-4905-9922-66090aa2e20c
Huang, Yande, Tao, Hongfeng, Chen, Yiyang, Rogers, Eric and Paszke, Wojciech
(2023)
Point-to-point iterative learning control with quantised input signal and actuator faults.
International Journal of Control.
(doi:10.1080/00207179.2023.2206496).
Abstract
This paper applies iterative learning control to point-to-point tracking problems with a general networked structure. The data is quantised and transmitted through restricted communication channels from the controller to the actuator. Combining a logarithmic quantizer with an encoding and decoding mechanism to quantise the input signals reduces the influence of the quantisation error. New design algorithms are developed with conditions for convergence of the tracking error and an extension to fault-tolerant performance under actuator failures. A numerical-based case study demonstrates the application of the new designs, which includes a comparison with another ILC law and the relative merits of the encoding and decoding schemes.
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Point-to-point iterative learning control with quantised input signal and actuator faults
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Accepted/In Press date: 16 April 2023
e-pub ahead of print date: 22 May 2023
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Publisher Copyright:
© 2023 Informa UK Limited, trading as Taylor & Francis Group.
Keywords:
Iterative learning control, encoding-decoding mechanism, fault-tolerant, optimal design, quantised input signal
Identifiers
Local EPrints ID: 479175
URI: http://eprints.soton.ac.uk/id/eprint/479175
ISSN: 0020-3270
PURE UUID: 8490478d-dc02-4574-ab61-3aecd8dad595
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Date deposited: 20 Jul 2023 16:42
Last modified: 18 Mar 2024 02:38
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Contributors
Author:
Yande Huang
Author:
Hongfeng Tao
Author:
Yiyang Chen
Author:
Eric Rogers
Author:
Wojciech Paszke
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