The Selection of Cost Functions in Model Predictive Control Applications

Author(s):  
Marco Rivera ◽  
Diego Rojas ◽  
Patrick Wheeler
Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 31 ◽  
Author(s):  
Van-Quang-Binh Ngo ◽  
Minh-Khai Nguyen ◽  
Tan-Tai Tran ◽  
Young-Cheol Lim ◽  
Joon-Ho Choi

In this paper, a model predictive control scheme for the T-type inverter with an output LC filter is presented. A simplified dynamics model is proposed to reduce the number of the measurement and control variables, resulting in a decrease in the cost and complexity of the system. Furthermore, the main contribution of the paper is the approach to evaluate the cost function. By employing the selection of sector information distribution in the reference inverter voltage and capacitor voltage balancing, the execution time of the proposed algorithm is significantly reduced by 36% compared with conventional model predictive control without too much impact on control performance. Simulation and experimental results are studied and compared with conventional finite control set model predictive control to validate the effectiveness of the proposed method.


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