Nonexcessive-ΔV and Low Complexity Model Predictive Control Based on Finite-State Machine for Three-Level Three-Phase Inverters

For three-level three-phase inverters, a novel finite-state machine-based model predictive control (FSM-MPC) is proposed. The state transition diagram of FSM is regarded as the operation guideline to avoid excessive voltage jumps (Δ V ). No more than five voltage vectors (VVs) are selected as FSM-MPC's candidates VVs, based on the VV reference and the previous optimal VV. And the cost function is simplified in terms of time duration. Thus, evaluating a candidate VV requires a very low computation cost. Without losing control performance, the proposed FSM-MPC's execution time is decreased to 50% of the MPC algorithm, which enumerates all basic VVs to get global optimal VV and performance. Compared with the existing simplified algorithms, the proposed FSM-MPC makes current harmonics lower, and its average switching frequency is 33% less, which means much less switching loss. Furthermore, the proposed algorithm is robust when the electric-circuit parameters are mismatched in the control system. Experimental results are provided to validate the advantages of the proposed algorithm.