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Interval type-2 fuzzy logic control for a space nuclear reactor core power system

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  • Zhao, Chengxuan
  • Yang, Xiao
  • Yu, Jie
  • Yang, Minghan
  • Wang, Jianye
  • Chen, Shuai

Abstract

The uncertain environment and delayed communications bring great challenges for the space nuclear reactor core power control. The imprecise knowledge about nonlinear and time varying parameters of the reactor make the problem further difficult. In this work, an anti-interference method is proposed for the core power control of space reactors. A new core power controller is designed to compensate the power deviation caused by model uncertainties and external disturbances. To further approximate nonlinear mapping functions between the control drum angle position and the deviation of the reactor core power, an interval type-2 fuzzy logic system is employed to deduce the correction of control drum angle position for its general approximation ability. Moreover, in order to solve control difficulties caused by physical constraints of the control drum and high stability requirements of the core power control system, an optimized iteration algorithm is proposed to ensure convergence to the optimal solution. A 1MWe space nuclear reactor is used as a reference object to carry out the research and verification of the newly proposed power control scheme. The numerical results verify the feasibility of the novel controller and show that load tracking performance of the system can be realized effectively.

Suggested Citation

  • Zhao, Chengxuan & Yang, Xiao & Yu, Jie & Yang, Minghan & Wang, Jianye & Chen, Shuai, 2023. "Interval type-2 fuzzy logic control for a space nuclear reactor core power system," Energy, Elsevier, vol. 280(C).
    • Handle: RePEc:eee:energy:v:280:y:2023:i:c:s0360544223014962
    DOI: 10.1016/j.energy.2023.128102
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    References listed on IDEAS

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    Cited by:

    1. Ma, Wenkui & Ye, Ping & Gao, Yue & Hao, Yadong & Yang, Xiaoyong, 2024. "Optimization of thermodynamic performance and mass evaluation for MW-class space nuclear reactor coupled with noble gas binary mixtures Brayton cycle," Energy, Elsevier, vol. 293(C).
    2. Zhou, Shiqi & Lin, Meng & Huang, Shilong & Xiao, Kai, 2024. "Open set compound fault recognition method for nuclear power plant based on label mask weighted prototype learning," Applied Energy, Elsevier, vol. 369(C).

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