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Post-combustion CO \(_2\) capture (PCC) plants stand as pivotal technologies for mitigating carbon emissions. The estimation and control of PCC pose significant challenges due to the large-scale and intricate nonlinear dynamics of the plants. This study focuses on state estimation for the absorption column of a typical PCC plant, where the column is discretized along its axial position. An extended Kalman filtering is designed to estimate the state across the entire column. Comprehensive simulation results illustrate the effectiveness of the proposed method.

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State Estimation for the Absorption Column of PCC Plants Using the Extended Kalman Filtering

  • 会议论文

  • 发表日期：

    2025年

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  • Siyu Liu,
  • Yonghua Jiang,
  • Xiao Zhang,
  • Feiyan Chen

摘要

Post-combustion CO \(_2\) capture (PCC) plants stand as pivotal technologies for mitigating carbon emissions. The estimation and control of PCC pose significant challenges due to the large-scale and intricate nonlinear dynamics of the plants. This study focuses on state estimation for the absorption column of a typical PCC plant, where the column is discretized along its axial position. An extended Kalman filtering is designed to estimate the state across the entire column. Comprehensive simulation results illustrate the effectiveness of the proposed method.