2025 lEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE 2025)

Finite control set MPC is widely used in power electronics converters as it eliminates the need for a modulator, directly handling switching actions. However, this results in higher switching frequencies, often requiring a single-sample horizon to maintain computational feasibility at the cost of dynamic performance. To address the computational burden of FCS-MPC, various techniques have been proposed. This paper builds on two established approaches: the subset of adjacent vectors (SAV) and the sphere decoding algorithm (SDA), which optimizes computations by reducing the search space. A novel technique, Preselected Adjacent Vectors with Sphere Decoding Algorithm (PAV-SDA), is introduced. The proposed approach is implemented in a three-phase two-level voltage source inverter (3P-2L-VSI) and evaluated through simulations. 
The findings demonstrate that PAV-SDA achieves a balance between computational efficiency and performance. For longer horizons, PAV-SDA significantly reduces computational effort compared to standard FCS-MPC while maintaining THD and MSE values. 

power electronics control,subset of adjacent vectors,computational burden reduction,search space reduction