Reduction of Prediction Errors for the Matrix Converter with an Improved Model Predictive Control

Shuang Feng, Chaofan Wei and Jiaxing Lei
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Shuang Feng: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Chaofan Wei: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Jiaxing Lei: School of Electrical Engineering, Southeast University, Nanjing 210096, China

Energies, 2019, vol. 12, issue 15, 1-20

Abstract: In this paper, an improved model predictive control (MPC) is proposed for the matrix converter (MC). First, the conventional MPC which adopts the separately discretized prediction models is discussed. It shows that the conventional MPC ignores the input–output interaction in every sampling period. Consequently, additional prediction errors arise, resulting in more current harmonics. Second, the principle of the improved MPC is presented. With the interaction considered, the integral state-space equation of the whole MC system is constructed and discretized to obtain the precise model. The eigenvalue analysis shows that the proposed prediction model has the same eigenvalues with the continuous model, and thus is more accurate than the conventional one to describe the MC’s behavior in every sampling period. Finally, experimental results under various working conditions prove that the proposed approach can always increase the control accuracy and reduce the harmonic distortions, which in turn requires smaller filter components.

Keywords: matrix converter; model predictive control; prediction model; prediction error; current harmonics (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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