Multi-Agent DDPG-Based DC-Link Voltage Balancing Control for Cascaded H-Bridge Rectifiers

Cascaded H-bridge rectifiers suffer from severe DC-link voltage imbalance under unbalanced load conditions. Considering the difficulties of parameter tuning and unsatisfactory dynamic response of traditional voltage balancing control schemes under complex nonlinear operating conditions, this study proposes an intelligent voltage balancing strategy based on the multi-agent deep deterministic policy gradient (DDPG) algorithm. By constructing an interactive environment between multiple agents and the cascaded H-bridge rectifier, the proposed method enables the agents to autonomously optimize control commands and realize DC-link voltage balance. The proposed method adopts a centralized training and decentralized execution framework to enable coordinated control among submodules. The simulation and hardware-in-the-loop (HIL) experimental results demonstrate that the proposed strategy can effectively suppress DC-link voltage imbalance and improve dynamic performance. Specifically, compared with conventional voltage balancing methods, the maximum total output voltage deviation is reduced from approximately 85 V to 45 V in HIL experiments, while the voltage settling time is shortened from about 260 ms to 120 ms. These results indicate that the proposed method can effectively eliminate steady-state errors and achieve fast and stable DC-link voltage balancing even under severely unbalanced load conditions.