- Title
- Computationally efficient model predictive control for AC-DC-AC converter with common mode voltage elimination
- Creator
- Uddin, Muslem; Mirzaeva, Galina; Goodwin, Graham; Zanchetta, Pericle
- Publisher Link
- http://dx.doi.org/10th Annual IEEE Energy Conversion Congress and Exposition. Proceedings of the 2018 IEEE Energy Conversion Congress and Exposition (ECCE) (Portland, OR 23-27 September, 2018) p. 6418-6423
- Publisher Link
- http://dx.doi.org/10.1109/ECCE.2018.8557733
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2018
- Description
- This paper proposes a computationally efficient modified model predictive control (MMPC) method for AFE-rectifier based AC-DC-AC converter system, to eliminate the common-mode-voltage (CMV) without any degradation of harmonic profile of the load current, as well as to significantly reduce the computational time of the predictive algorithm. The proposed MMPC method is formulated in voltage domain rather than current domain as in traditional MPC method. In the proposed MMPC method, sector pre-determination is adopted, to reduce the available finite-control-set (FCS), which significantly reduces the computational time for the predictive algorithm. Also, CMV is eliminated by applying synchronization between the rectifier and inverter parts of AFE-rectifier based AC-DC-AC converter, when selecting the optimal switching combination for the next sampling interval. The proposed MMPC method is verified in MATLAB-Simulink. The results confirm that the proposed method achieve the following outcomes: significantly reduces the computational time, completely eliminates the CMV without degradation of harmonic content, and opens the door to improve the power quality in any CMV sensitive industry applications by utilizing faster sampling frequency.
- Subject
- predictive control; common mode voltage; AC-DC-AC converter; cost function; synchronization
- Identifier
- http://hdl.handle.net/1959.13/1405066
- Identifier
- uon:35438
- Identifier
- ISBN:9781479973125
- Language
- eng
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