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Open AccessJournal ArticleDOI

Multistep Finite Control Set Model Predictive Control for Power Electronics

Tobias Geyer, +1 more
- 19 Feb 2014 - 
- Vol. 29, Iss: 12, pp 6836-6846
TLDR
In this article, an efficient optimization algorithm for direct model predictive control with reference tracking of the converter current is proposed. But the computational burden of the algorithm is independent of the number of converter output levels, the concept is particularly suitable for multi-level topologies with a large number of voltage levels.
Abstract
For direct model predictive control with reference tracking of the converter current, we derive an efficient optimization algorithm that allows us to solve the control problem for very long prediction horizons. This is achieved by adapting sphere decoding principles to the underlying optimization problem. The proposed algorithm requires only few computations and directly provides the optimal switch positions. Since the computational burden of our algorithm is effectively independent of the number of converter output levels, the concept is particularly suitable for multi-level topologies with a large number of voltage levels. Our method is illustrated for the case of a variable speed drive system with a three-level voltage source converter.

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Citations
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Journal ArticleDOI

Model Predictive Control for Power Converters and Drives: Advances and Trends

TL;DR: The paper revisits the operating principle of MPC and identifies three key elements in the MPC strategies, namely the prediction model, the cost function, and the optimization algorithm.
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Model Predictive Control: MPC's Role in the Evolution of Power Electronics

TL;DR: In this article, the authors present a review of the history of power converter control with an emphasis on the more recent introduction of predictive control, and give a glimpse on the challenges and possibilities ahead.
Journal ArticleDOI

Model Predictive Current Control for PMSM Drives With Parameter Robustness Improvement

TL;DR: Simulation and experimental results both show that the proposed method can effectively eliminate the influence of the parameter mismatches on the control performance and reduce the parameter sensitivity of the MPCC method.
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Guidelines for the Design of Finite Control Set Model Predictive Controllers

TL;DR: This article discusses and analyzes the factors that affect the closed-loop performance of FCS-MPC and design guidelines are provided that help to maximize the system performance.
Journal ArticleDOI

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

TL;DR: In this paper, a modified sphere decoding algorithm is used to efficiently solve the optimization problem underlying direct model predictive control (MPC) for long horizons, and the computational burden is reduced by four orders of magnitude, compared to the standard exhaustive search approach.
References
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TL;DR: In this article, the authors present results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrate their importance in a variety of applications, such as linear algebra and matrix theory.
Journal ArticleDOI

The explicit linear quadratic regulator for constrained systems

TL;DR: A technique to compute the explicit state-feedback solution to both the finite and infinite horizon linear quadratic optimal control problem subject to state and input constraints is presented, and it is shown that this closed form solution is piecewise linear and continuous.
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