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Iterative Learning Control for Completely Uncertain CSTR with Matched Disturbance

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Advances in Engineering Research and Application (ICERA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 602))

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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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Author information

Authors and Affiliations

  1. Hanoi University of Science and Technology, Hanoi, Vietnam

    Trung Thanh Cao, Nam Hoai Nguyen & Phuoc Doan Nguyen

Authors
  1. Trung Thanh Cao
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  2. Nam Hoai Nguyen
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  3. Phuoc Doan Nguyen
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Corresponding author

Correspondence to Trung Thanh Cao .

Editor information

Editors and Affiliations

  1. Faculty of Electronic Engineering, Thai Nguyen University of Technology, Thai Nguyen, Vietnam

    Duy Cuong Nguyen

  2. Faculty of Mechanical Engineering, Thai Nguyen University of Technology, Thai Nguyen, Vietnam

    Ngoc Pi Vu

  3. Vietnam Association for Science Editing, Hanoi University of Science and Technology, Hanoi, Vietnam

    Banh Tien Long

  4. Institute for Automation and Systems Engineering, Ilmenau University of Technology (IUT), Ilmenau, Germany

    Horst Puta

  5. Department of Computer Science and Automation, Ilmenau University of Technology (IUT), Ilmenau, Germany

    Kai-Uwe Sattler

Appendix

Appendix

The source code of simulation program ICERA2022.m written in MatLab is as below.

figure a
figure b

The aforementioned simulation program uses following subprogram for the declaration of CSTR dynamic.

figure c

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Cao, T.T., Nguyen, N.H., Nguyen, P.D. (2023). Iterative Learning Control for Completely Uncertain CSTR with Matched Disturbance. In: Nguyen, D.C., Vu, N.P., Long, B.T., Puta, H., Sattler, KU. (eds) Advances in Engineering Research and Application. ICERA 2022. Lecture Notes in Networks and Systems, vol 602. Springer, Cham. https://doi.org/10.1007/978-3-031-22200-9_68

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

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22199-6

  • Online ISBN: 978-3-031-22200-9

  • eBook Packages: EngineeringEngineering (R0)

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