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Auto-balanced Multi-MPC control of a SOFC system based on included angle

Author

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  • Du, Jingjing
  • Chen, Junfeng
  • Li, Jian

Abstract

This article studies the Multi-model predictive control (Multi-MPC) of a solid oxide fuel cell (SOFC) system. SOFCs have numerous advantages, such as clean operation, all-solid-state structure, high efficiency, and high reliability, making them an ideal candidate for renewable energy systems. However, designing an effective controller for a SOFC system is challenging due to its strong nonlinearity and complexity. In this work, we analyze the dynamic and static characteristics of a SOFC system in detail and find it with the special Hammerstein-Wiener model structure. Therefore, we employ the included angle (IA) to measure the system's nonlinearity and propose an auto-balanced multi-model decomposition (MMD) method based on IA to decompose the system into linear sub-models effectively. Based on the balanced MMD result, linear MPCs are designed, and further combined into a Multi-MPC via IA-based weighting functions (IAWFs). Closed-loop simulations demonstrate that the proposed Multi-MPC, based on the IA-based auto-balanced MMD and IAWFs, outperforms other controllers in terms of stability, accuracy, and robustness.

Suggested Citation

  • Du, Jingjing & Chen, Junfeng & Li, Jian, 2025. "Auto-balanced Multi-MPC control of a SOFC system based on included angle," Renewable Energy, Elsevier, vol. 249(C).
    • Handle: RePEc:eee:renene:v:249:y:2025:i:c:s0960148125008675
    DOI: 10.1016/j.renene.2025.123205
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