A new digital control method for a voltage source inverter to compensate for imbalance of output voltage

2012 ◽  
Vol 41 (8) ◽  
pp. 879-888 ◽  
Author(s):  
Jian-Min Wang ◽  
Po-Jung Tseng ◽  
Shang-Chin Yen ◽  
Pang-Jung Liu ◽  
Huang-Jen Chiu
Author(s):  
Nik Fasdi Nik Ismail ◽  
Norazlan Hashim ◽  
Dalina Johari

This paper presents the analysis study between multilevel inverters that are often classified into multilevel voltage source and multilevel current source inverters.  For multilevel voltage source inverter (MVSI), the specific topology studied for this work is the Cascaded H-Bridge MVSI.  Whereas, the multilevel current source inverter (MCSI) is based on Paralleled Inductor Configuration MCSI.  For this study, the analysis between these converters are done with respect to the number of components, the advantages and disadvantages of each converters during performing inverter operation. In term of output voltage and current quality, the percentage of the Total Harmonic Distortion (THD) are measured and compared for both topologies.  MATLAB/Simulink software has been used in this research to design and simulate in order to study the performances of both inverters.


Author(s):  
Atif Iqbal ◽  
Shaikh Moinoddine ◽  
Khaliqur Rahman

<p class="abstract">The paper elaborate finite set model based predictive current control of a seven-phase voltage source inverter. The current control is carried out considering a finite set of control actions. The space vector model of a seven-phase voltage source inverter (VSI) yields 2<sup>7</sup> = 128 space voltage vectors, with 126 active and two zero vectors. The control method described in this paper discard some switching states from the whole set and employs reduced number of switching states to track the commanded current. Three sets of space vectors are used for switching actuation, in one case only 15 vectors are used (14 active and one zero), in second case 29 vectors are used (28 active and one zero) and finally 43 vectors (42 active and one zero) are employed. Optimal algorithm is employed to find the vector which minimizes the chosen cost function. The effect of selecting the cost function, the number of space vectors and the sampling time is investigated and reported. The developed technique is tested for RL load using simulation and experimental approaches.</p><p class="Papertitle"> </p>


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