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Gain scheduled internal model control based on the dynamic sliding mode method for the water level of nuclear steam generators

  • Farzaneh Farzampanah and GholamReza Ansarifar EMAIL logo
Published/Copyright: April 19, 2024
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Abstract

The Steam Generator (SG) is a crucial component of a nuclear power plant. Proper water level control in a nuclear steam generator is of great importance to ensure a sufficient cooling source for the nuclear reactor and to prevent damage to turbine blades. The water level control problem of steam generators has been a leading cause of unexpected shutdowns in nuclear power plants, which must be addressed for plant safety and availability. The control problem is challenging, particularly at low power levels due to shrink and swell phenomena and flow measurement errors. Furthermore, the dynamics of the steam generator vary as the power level changes. Therefore, there is a need to enhance the water level control system of the SG. In this paper, a Gain Scheduled Internal Model Control (IMC) based on the Dynamic Sliding Mode (DSMC) method is developed for the level control problem. The proposed method exhibits the desired dynamic properties throughout the entire output tracking process, independent of perturbations. Simulation results are presented to demonstrate the effectiveness of the proposed controller in terms of performance, robustness, and stability. The simulation results confirm the improvement in transient response achieved by using the proposed controller.


Corresponding author: GholamReza Ansarifar, Department of Nuclear Engineering, Faculty of Physics, University of Isfahan, 81746-73441 Isfahan, Iran, E-mail:

  1. Research ethics: The local Institutional Review Board deemed the study exempt from review.

  2. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: The authors state no conflict of interest.

  4. Research funding: None declared.

  5. Data availability: The raw data can be obtained on request from the corresponding author.

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Received: 2023-12-01
Accepted: 2024-03-28
Published Online: 2024-04-19
Published in Print: 2024-06-25

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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