Long-horizon direct model predictive control with active balancing of the neutral point potential
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE) |
| Publisher | IEEE |
| Pages | 89 - 94 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-1-5386-0507-3 |
| DOIs | |
| Publication status | Published - Sep 2017 |
| Publication type | A4 Article in a conference publication |
| Event | IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics - Duration: 1 Jan 1900 → … |
Conference
| Conference | IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics |
|---|---|
| Period | 1/01/00 → … |
Abstract
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.
Publication forum classification
Field of science, Statistics Finland
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