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2023 | OriginalPaper | Chapter

Iterative Learning Control for Completely Uncertain CSTR with Matched Disturbance

Authors : Trung Thanh Cao, Nam Hoai Nguyen, Phuoc Doan Nguyen

Published in: Advances in Engineering Research and Application

Publisher: Springer International Publishing

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Abstract

This paper proposes an intelligent controller for output tracking control for a completely uncertain two-state continuous stirred tank reactor (CSTR) with disturbance on input. This control method is established by combining the concept of iterative learning control (ILC) and a model-free disturbance estimator for compensating purpose. Hence, the created controller does not use the original nonlinear model of CSTR or linearize it around operating points as usual. In consequence, all unexpected performances, which are inevitability caused by switching the control between linear subsystems, are prevented. The effectiveness of proposed approach had been authenticated by an illustrative simulation.

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Appendix
Available only for authorised users
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Metadata
Title
Iterative Learning Control for Completely Uncertain CSTR with Matched Disturbance
Authors
Trung Thanh Cao
Nam Hoai Nguyen
Phuoc Doan Nguyen
Copyright Year
2023
Book
Advances in Engineering Research and Application

Print ISBN: 978-3-031-22199-6

Electronic ISBN: 978-3-031-22200-9

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-3-031-22200-9_68

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