RT Journal Article
T1 Long-Prediction Horizon FCS-MPC for Multiphase Electric Drives With a Selective Control Action Promotion
A1 Carrillo Ríos, Juan
A1 González Prieto, Ignacio
A1 González Prieto, Ángel
A1 Durán-Martínez, Mario Javier
A1 Aciego Gallardo, Juan José
K1 Electrónica industrial
K1 Control automático
AB Model predictive control (MPC) is an interesting regulation solution in the field of multiphase electric drives. Its performance has been improved from different perspectives, but most works implement a single-step horizon approach. The complexity of using long-prediction horizons along with the higher complexity of multiphase systems has hindered the real-time implementation of multistep strategies. In fact, the only attempt of designing a multistep solution for multiphase drives uses a smart selection of the voltage vector, reducing the computational burden. Unfortunately, this strategy completely disregards the voltage output selected as the better candidate in the second step (i.e., in k+3), hence missing valuable information that can be inherited from one sampling period to the next one. This work suggests informing the MPC by creating a so-called hall of fame that stores the switching state determined as a suitable candidate in the previous sampling time. Such vector is promoted in the iterative process by adding a term in the cost function that is activated when the switching state under evaluation is within the hall of fame. Experimental results in a six-phase drive confirm the capability of the proposed scheme to simultaneously improve the current tracking and reduce the switching frequency.
PB IEEE
YR 2023
FD 2023-11-22
LK https://hdl.handle.net/10630/39978
UL https://hdl.handle.net/10630/39978
LA eng
NO J. Carrillo-Ríos, I. González-Prieto, Á. González-Prieto, M. J. Durán and J. J. Aciego, "Long-Prediction Horizon FCS-MPC for Multiphase Electric Drives With a Selective Control Action Promotion," in IEEE Transactions on Industrial Electronics, vol. 71, no. 9, pp. 9982-9993, Sept. 2024, doi: 10.1109/TIE.2023.3329230.
NO https://openpolicyfinder.jisc.ac.uk/id/publication/3475
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026