Performance of Multistep Finite Control Set Model Predictive Control for Power Electronics
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 alg...
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Veröffentlicht in: | IEEE transactions on power electronics 2015-03, Vol.30 (3), p.1633-1644 |
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description | 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. |
doi_str_mv | 10.1109/TPEL.2014.2316173 |
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subjects | Algorithms Computation Electronics Horizon Inverters Mathematical models Modulation Optimization Predictive control Searching Support vector machines Switches Switching Switching frequency Vector space |
title | Performance of Multistep Finite Control Set Model Predictive Control for Power Electronics |
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