4.8 Article

Performance of Multistep Finite Control Set Model Predictive Control for Power Electronics

Journal

IEEE TRANSACTIONS ON POWER ELECTRONICS
Volume 30, Issue 3, Pages 1633-1644

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPEL.2014.2316173

Keywords

Branch and bound; drive systems; finite control set; model predictive control (MPC); power electronics; quantization; sphere decoding

Funding

  1. Australian Research Council [DP 110103074]
  2. ABB Corporate Research, Switzerland
  3. University of Auckland, New Zealand

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The performance of direct model predictive control (MPC) with reference tracking and long prediction horizons is evaluated through simulations, using the current control problem of a variable speed drive system with a voltage source inverter as an illustrative example. A modified sphere decoding algorithm is used to efficiently solve the optimization problem underlying MPC for long horizons. For a horizon of five and a three-level inverter, for example, the computational burden is reduced by four orders of magnitude, compared to the standard exhaustive search approach. This paper illustrates the performance gains that are achievable by using prediction horizons larger than one. Specifically, for long prediction horizons and a low switching frequency, the total harmonic distortion of the current is significantly lower than for space vector modulation, making direct MPC with long horizons an attractive and computationally viable control scheme.

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