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With the transformation of national energy, in order to further absorb renewable energy, the optimization of control performance of ultra supercritical (USC) unit as representatives of clean and efficient development and utilization of coal is crucial. This paper proposes a nonlinear generalized predictive control algorithm (GPC) for ultra supercritical unit based on fuzzy C-means clustering algorithm (FCM). The unit operation process is divided into multiple local areas through FCM to reduce its nonlinearity; then the local controller is designed by GPC and the global controller is obtained through the weighted strategy, so as to achieve the purpose of improving the control performance of the unit. Finally, taking a 350 MW ultra supercritical unit as an example, the method is verified through simulation.

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Nonlinear Generalized Predictive Control Based FCM of an Ultra Supercritical Unit

  • 会议论文

  • 发表日期：

    2026年

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  • Shuyu Sun,
  • Wenxuan Ma,
  • Zhongrui Zhou,
  • Weiyan Liu

摘要

With the transformation of national energy, in order to further absorb renewable energy, the optimization of control performance of ultra supercritical (USC) unit as representatives of clean and efficient development and utilization of coal is crucial. This paper proposes a nonlinear generalized predictive control algorithm (GPC) for ultra supercritical unit based on fuzzy C-means clustering algorithm (FCM). The unit operation process is divided into multiple local areas through FCM to reduce its nonlinearity; then the local controller is designed by GPC and the global controller is obtained through the weighted strategy, so as to achieve the purpose of improving the control performance of the unit. Finally, taking a 350 MW ultra supercritical unit as an example, the method is verified through simulation.