شماره ركورد كنفرانس :
5060
عنوان مقاله :
Computation Reduction for Finite Set Model Predictive Control of Five-level Inverter
Author/Authors :
Alireza, Ja’afari Department of Electrical Engineering -Shahid Rajaee Teacher Training University، Tehran, Iran , Alireza ، Davari Department of Electrical Engineering -Shahid Rajaee Teacher Training University، Tehran, Iran , Cristian ، Garcia Department of Electrical Engineering - Universidad de Talca، Curico, Chile , Jose ، Rodriguez Dept. of Engineering - Universidad Andres Bello Santiago, Chile
كليدواژه :
Computational burden , Neutral Point Clamped (NPC) , Model Predictive Control (MPC) , multilevel inverter
عنوان كنفرانس :
11th Power Electronics, Drive Systems, and Technologies Conference (PEDSTC)
چكيده فارسي :
فاقد چكيده فارسي
چكيده لاتين :
Finite set model predictive control (FS-MPC) method is a method that requires the calculation of the cost function prediction due to the number of switching vectors on the power converter. As the number of vectors increases, so does the amount of computation. Nowadays, computational burden needs to be reduced due to the development of using FS-MPC in multilevel converters such as neutral point clamped (NPC) converter. This paper presents a method for reducing the computational burden for the fine-level NPC inverters in which only two candidates are included in the cost function among the available candidates. The rectangular area method is used in order to select the proper candidates for the cost function. The proposed method is evaluated by simulations.
