Open AccessTwo‐voltage hierarchical model predictive control for a single‐phase cascaded H‐bridge rectifier
Author(s) -
Qi Chen,
Chen Xiyou,
Su Lijuan,
Lang Zhengying
Publication year - 2019
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2018.5534
Subject(s) - control theory (sociology) , rectifier (neural networks) , model predictive control , weighting , computer science , duty cycle , voltage , control (management) , engineering , artificial intelligence , physics , stochastic neural network , recurrent neural network , artificial neural network , acoustics , electrical engineering
The finite‐control‐set model predictive control (FCS‐MPC) method is promising for cascaded H‐bridge (CHB) rectifiers. However, three issues arise in the traditional FCS‐MPC method: heavy computational burden, low steady‐state performance, and time‐consuming tuning work of weighting factor. Although some modified FCS‐MPC methods have been proposed for CHB rectifiers, there is an open task to solve all aforementioned issues simultaneously. Here, a novel FCS‐MPC method has been proposed for a single‐phase CHB rectifier. In proposed method, the computational burden is reduced from exponential time to linear time. The steady‐state performance is improved by selecting an optimal combination of two output voltages along with their duty cycles. The weighting factor is eliminated by using a hierarchical control structure. The proposed method has been tested and evaluated against three existing FCS‐MPC methods on a single‐phase three‐cell CHB rectifier.