The application of the finite control set model predictive control to cascaded inverters is severely limited by its computational complexity. In this paper, a load observer based multilayer model predictive control is proposed for the voltage mode digital power amplifier employing cascaded full-bridge neutral point clamped inverter, which can avoid the use of load current sensor and greatly reduce the controller computation without affecting its dynamic performance. The discrete mathematical model of the voltage mode digital power amplifier employing cascaded full-bridge neutral point clamped inverter is established with filter inductor current and filter capacitor voltage as state variables. A load current observer is designed based on this to avoid the use of load current observer. Based on the discrete model and the observed load current, the upper layer of the multilayer model predictive control determines the optimal level that minimizes the cost function. The middle layer allocates the optimal level to each submodule in order to achieve capacitor voltage balancing. The lower layer determines the switching state of each submodule in order to reduce switching actions. Finally, the experimental results based on the designed nine-level prototype show that the develop multilayer model predictive control lead to acceptable steady state, dynamic and robust performance, with only 1.37% of the run time of the traditional model predictive control.
Selective finite‐states model predictive control of grid interfaced three‐level neutral point clamped photovoltaic inverter for inherent capacitor voltage balancing