124 / 2025-03-14 15:35:29
Delay Compensated Reinforcement Learning Predictive Control for Power Converters
model predictive control,reinforcement learning,delay compensation,power converters,robustness
Final Paper
Chenghao Liu / Zhejiang University;the College of Electrical Engineering
Jien Ma / Zhejiang University;the College of Electrical Engineering
Lin Qiu / Zhejiang University;the College of Electrical Engineering
Xing Liu / Shanghai Dianji University
Youtong Fang / Zhejiang University;the College of Electrical Engineering
This paper proposes a delay compensated reinforcement learning predictive control (DC-RLPC) solution for power converters. More precisely, an actor critic-based intelligent agent is integrated into the predictive control framework, establishing a model-free approach that eliminates the reliance on physical information. It enhances the robustness of model predictive control by mitigating the effects of unknown or unmodeled dynamics. Furthermore, a novel delay compensated Bellman equation is proposed, and the corresponding RL training algorithm is developed to address the digital delay in control systems. It lays the foundation for future practical applications of RL. Finally, the effectiveness of the proposed DC-RLPC is validated through numerical examples.
Important Date
  • Conference Date

    Jun 05

    2025

    to

    Jun 01

    2026

  • May 30 2025

    Draft paper submission deadline

  • Jun 08 2025

    Registration deadline

Sponsored By
China Southeast University
IEEE Power Electronics Society
Jiangsu Association of Automation
Nanjing Section IE Chapter
Organized By
Southeast University