Tuning of Predictive Controllers for Five-Phase Drives
Agnieszka Kowal Gornig1, Manuel R. Arahal2, Federico Barrero3
1Kowal Gornig Agnieszka Department of Systems and Automation, University of Seville, Spain,
2Manuel R. Arahal, Department of Systems and Automation, University of Seville, Spain.
3Federico Barrero, Department of Electronic Engineering, University of Seville, Spain.
Manuscript received on 18 October 2018 | Revised Manuscript received on 27 October 2018 | Manuscript published on 30 October 2018 | PP: 57-63 | Volume-8 Issue-1, October 2018 | Retrieval Number: A5494108118/18©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Model Predictive Control is gaining attention as a versatile tool for multi-phase drives. In the direct digital control configuration the predictive controller can use a finite number of control actions. This allows the use of exhaustive optimization to derive the control action. Using a cost function it is possible to consider several control objectives, such as current, torque or flux tracking. Also, different additional criteria such as switching frequency, harmonic distortion or torque ripple can be considered. Tuning of the controller involves assigning a value to weighting factors used by the cost function. This has been studied in detail for predictive torque controllers. In this paper three design strategies for designing predictive current controllers are compared. The first uses fixed weighting factors, the second eliminates weighting factors by using a ranking based selection and the last considers a local optimization of the weighting factors
Keywords: Multiphase Systems, Model Predictive Control, Cost Function, Weighting Factors.
Scope of the Article: Predictive Analysis