TY - JOUR
T1 - Cooperative Decision-Making Approach for Multiobjective Finite Control Set Model Predictive Control Without Weighting Parameters
AU - Xie, Haotian
AU - Novak, Mateja
AU - Wang, Fengxiang
AU - Dragicevic, Tomislav
AU - Rodriguez, Jose
AU - Blaabjerg, Frede
AU - Kennel, Ralph
AU - Heldwein, Marcelo Lobo
N1 - Publisher Copyright:
IEEE
PY - 2024/5
Y1 - 2024/5
N2 - Finite control set model predictive control (FCS-MPC) has gained increasing popularity as an emerging control strategy for electrical drive systems. However, it is still a challenging task to optimize weighting parameters, as multiple objectives are involved in the customized cost function. A cooperative decision-making approach for FCS-MPC is proposed in this article, to solve the optimization problems with manifold control objectives. By splitting the cost function, the optimization problem underlying multiobjective FCS-MPC is separated into a series of decomposed optimization problems. By doing so, the dimension of the decomposed problem is reduced to one. To collect the information for decision-making, an efficient sorting algorithm is applied for each control objective. The theory behind the cooperative decision-making approach is comprehensively analyzed, to validate both the effectiveness and efficiency of the proposed scheme. More specifically, the highlight is the adaptive mechanism on the number of desired candidates, to obtain a decent performance for torque and flux. The candidate that minimizes the switching frequency is selected as the optimal. The proposed scheme is experimentally verified and compared with the existing FCS-MPC without weighting parameters.
AB - Finite control set model predictive control (FCS-MPC) has gained increasing popularity as an emerging control strategy for electrical drive systems. However, it is still a challenging task to optimize weighting parameters, as multiple objectives are involved in the customized cost function. A cooperative decision-making approach for FCS-MPC is proposed in this article, to solve the optimization problems with manifold control objectives. By splitting the cost function, the optimization problem underlying multiobjective FCS-MPC is separated into a series of decomposed optimization problems. By doing so, the dimension of the decomposed problem is reduced to one. To collect the information for decision-making, an efficient sorting algorithm is applied for each control objective. The theory behind the cooperative decision-making approach is comprehensively analyzed, to validate both the effectiveness and efficiency of the proposed scheme. More specifically, the highlight is the adaptive mechanism on the number of desired candidates, to obtain a decent performance for torque and flux. The candidate that minimizes the switching frequency is selected as the optimal. The proposed scheme is experimentally verified and compared with the existing FCS-MPC without weighting parameters.
KW - Model predictive control
KW - Multiple objectives
KW - Optimization
KW - Power Electronics
KW - cooperative decision-making
KW - weighting parameters optimization
UR - http://www.scopus.com/inward/record.url?scp=85162706240&partnerID=8YFLogxK
U2 - 10.1109/TIE.2023.3283689
DO - 10.1109/TIE.2023.3283689
M3 - Journal article
AN - SCOPUS:85162706240
SN - 0278-0046
VL - 71
SP - 4495
EP - 4506
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 5
M1 - 10149167
ER -