Online Weighting Factor Optimization by Simplified Simulated Annealing for Finite Set Predictive Control

Model predictive control brings many advantages and it simplifies the control scheme in power electronics. However, tuning the weighting factor is one of the important open discussions on this topic. There are online and offline methods that have been introduced to select the weighting factor. The o...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2021-01, Vol.17 (1), p.31-40
Main Authors: Davari, S. Alireza, Nekoukar, Vahab, Garcia, Cristian, Rodriguez, Jose
Format: Article
Language:English
Subjects:
Convergence
Cost function
Induction motors
Informatics
Optimization
Predictive control
Search algorithms
simplified simulated annealing (SA)
Simulated annealing
Stators
Torque
Weighting
weighting factor
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Summary:Model predictive control brings many advantages and it simplifies the control scheme in power electronics. However, tuning the weighting factor is one of the important open discussions on this topic. There are online and offline methods that have been introduced to select the weighting factor. The online methods are preferred because they are more feasible. In this article, an online weighting factor optimization method based on the simulated annealing algorithm is proposed. The energy of the ripple is used as a convergence criterion. The presented method can be converged in a few steps and it does not impose cumbersome computations. Therefore, the optimal voltage will be identical for a range of the weighting factor. Furthermore, the used search algorithm is parameter independent. The proposed method is implemented for an induction motor but it is also applicable for other applications. The proposed method is validated by the experimental tests.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2020.2981039