Explicit model predictive control (EMPC) has attracted extensive attention in the field of power electronics owing to its excellent dynamic performance. However, the implementation of EMPC in hardware poses considerable challenges as it requires a large amount of computing resources for online computation. In this regard, this paper proposes to use a double rectified linear unit (DualReLU) artificial neural network (ANN) to approximate EMPC. Experimental results show that the proposed DualReLU ANN can effectively approximate EMPC while significantly reducing computational load and memory usage requirements.
