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2023 | OriginalPaper | Buchkapitel

Iterative Learning Control for Completely Uncertain CSTR with Matched Disturbance

verfasst von : Trung Thanh Cao, Nam Hoai Nguyen, Phuoc Doan Nguyen

Erschienen in: Advances in Engineering Research and Application

Verlag: 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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Titel: Iterative Learning Control for Completely Uncertain CSTR with Matched Disturbance
verfasst von: Trung Thanh Cao
Nam Hoai Nguyen
Phuoc Doan Nguyen
Verlag: Springer International Publishing
Buch: Advances in Engineering Research and Application
Print ISBN: 978-3-031-22199-6

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

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-3-031-22200-9_68

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