Nonexcessive-ΔV and Low Complexity Model Predictive Control Based on Finite-State Machine for Three-Level Three-Phase Inverters
Author:
Affiliation:
1. School of Automation, Central South University, Hunan, China
2. Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hunan Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/63/10130046/10105455.pdf?arnumber=10105455
Reference27 articles.
1. Low Complexity Model Predictive Flux Control for Three-Level Neutral-Point Clamped Inverter-Fed Induction Motor Drives Without Weighting Factor
2. Model Predictive Controller With Reduced Complexity for Grid-Tied Multilevel Inverters
3. TABLE‐BASED direct power control for three‐level neutral point‐clamped pulse‐width modulated rectifier
4. An Improved Direct Torque Control for Three-Level Inverter-Fed Induction Motor Sensorless Drive
5. Double Vector Model Predictive Control to Reduce Common-Mode Voltage Without Weighting Factors for Three-Level Inverters
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1. A Novel Extended Sliding-Mode Predictive Control With Dynamic Optimization and Virtual Voltage Vectors;IEEE Transactions on Power Electronics;2024-09
2. Cell-by-Cell-Based Finite Control Set Model Predictive Control for Paralleled Three-Phase Three-Level Inverters;IEEE Transactions on Industrial Electronics;2024
3. Low-Complexity Virtual-Vector Based FCS-MPC with Unaffected Neutral-Point Voltage for Three-Phase T-Type Inverters;IEEE Journal of Emerging and Selected Topics in Power Electronics;2024
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