Long-Horizon Direct Model Predictive Control With Active Balancing of the Neutral Point Potential

In this paper we present modifications to the sphere decoder initially introduced in [1] to include the control of the neutral point (NP) potential of a three-level neutral point clamped (NPC) inverter. By linearizing the system model, the nonlinearities introduced by the dynamics of the NP potential are discarded. As a result, the optimization problem underlying direct model predictive control (MPC) can be formulated as an integer least-squares (ILS) one, and solved in a computationally efficient manner with a refined sphere decoding algorithm. As shown, thanks to the utilization of long prediction horizons, the system performance can be significantly improved. This is demonstrated with a variable speed drive consisting of a threelevel NPC inverter and a medium-voltage induction machine.     «

In this paper we present modifications to the sphere decoder initially introduced in [1] to include the control of the neutral point (NP) potential of a three-level neutral point clamped (NPC) inverter. By linearizing the system model, the nonlinearities introduced by the dynamics of the NP potential are discarded. As a result, the optimization problem underlying direct model predictive control (MPC) can be formulated as an integer least-squares (ILS) one, and solved in a computationally...     »