.png){kind=icon}
.png){kind=icon}
Return
Multiobjective Modulated Model Predictive Control for a Multilevel Solid-State Transformer
.png){kind=icon}
OA
AI
DOI：10.1109/TIA.2015.2429113.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Finite control set model predictive control (FCS-MPC) offers many advantages over more traditional control techniques, such as the ability to avoid cascaded control loops, easy inclusion of constraint, and fast transient response of the control system. This control scheme has been recently applied to several power conversion systems, such as two, three, or more level converters, matrix converters, etc. Unfortunately, because of the lack of the presence of a modulation strategy, this approach produces spread spectrum harmonics which are difficult to filter effectively. This may result in a degraded power quality when compared to more traditional control schemes. Furthermore, high switching frequencies may be needed, considering the limited number of switching states in the converter. This paper presents a novel multiobjective modulated predictive control strategy, which preserves the desired characteristics of FCS-MPC but produces superior waveform quality. The proposed method is validated by experimental tests on a seven-level cascaded H-bridge back-to-back converter and compared to a classic MPC scheme.
Keywords:
AC-AC power conversion
ac-dc power conversion
model predictive control
power control
power conversion
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.5
Papers:
1.1W
Citations:
3.5W