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 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.

Automated summary

This article introduces an online weighting factor optimization method based on the simulated annealing algorithm, which converges in a few steps using ripple energy as a convergence criterion and does not require cumbersome computations. It is applicable for an induction motor as well as other applications, and has been validated through experimental tests.