Long-horizon direct model predictive control with active balancing of the neutral point potential
Liegmann, Eyke; Karamanakos, Petros; Geyer, Tobias; Mouton, Toit; Kennel, Ralph (2017-09)
Liegmann, Eyke
Karamanakos, Petros
Geyer, Tobias
Mouton, Toit
Kennel, Ralph
IEEE
09 / 2017
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202002262379
https://urn.fi/URN:NBN:fi:tuni-202002262379
Kuvaus
Peer reviewed
Tiivistelmä
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 three-level NPC inverter and a medium-voltage induction machine.
Kokoelmat
- TUNICRIS-julkaisut [17001]