Low-Complexity Finite Set Model Predictive Control for Split-Capacitor ANPC Inverter With Different Levels Modes and Online Model Update

In this article, an improved finite-control-set model predictive control (FCS-MPC) is presented for an active neutral point clamped (ANPC) topology. The considered converter significantly reduces the required power electronics components compared with other common dc-link converters, where only seven active switches, one bidirectional switch, and two floating capacitors (FCs) are employed to produce nine levels in the phase voltage. The developed FCS-MPC handles three control objectives with only one weighting factor, namely, current control, FC balancing, and NP potential stabilization, which reduces the cumbersome effort required for weighting factors coordination. In addition, the number of iterations required to identify the optimal vector is significantly reduced, which, in turn, reduces the execution time of the algorithm. The proposed control method empowers the considered converter to operate in different modes under the faulty condition of the bidirectional switch without any structure modification, which guarantees continuous operation of the converter while ensuring the balancing of FCs and dc-link capacitors in all operating modes. The sensitivity of the proposed FCS-MPC to parameter mismatch, which is a basic issue of MPC-based techniques, is tackled by employing an extended Kalman filter (EKF) to online estimate the system parameters. The proposed FCS-MPC algorithm is experimentally validated and compared with the conventional FCS-MPC method under different operating conditions.