Open AccessSelf‐tuning indirect adaptive control of non‐inverting buck–boost converter
Author(s) -
Hajizadeh Amin,
Shahirinia Amir H.,
Namjoo Navid,
Yu David C.
Publication year - 2015
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.2014.0492
Subject(s) - control theory (sociology) , buck converter , controller (irrigation) , converters , adaptive control , computer science , digital control , buck–boost converter , boost converter , stability (learning theory) , ćuk converter , control (management) , electronic engineering , voltage , engineering , artificial intelligence , machine learning , electrical engineering , biology , agronomy
This study presents an approach to system identification and adaptive control of a non‐inverting buck–boost converter in the presence of large signal changes, uncertainty of converter components and effects of imperfect modelling. Feedback loops of DC–DC converters are typically designed conservatively so that the closed‐loop regulation and stability margins are maintained over a pre‐determined range of operating conditions. The proposed approach is able to keep a high‐performance response without the instability issue of dynamic change of the converter. In the presence of uncertainty on the parameters of a DC–DC converter, a digital adaptive controller based on system identification and minimum degree pole placement is proposed. To verify the validity of the proposed digital controller, an experimental setup is constructed for a non‐inverting buck–boost converter and the fully digital adaptive control is implemented by a micro controller. The experimental results show the capability of an adaptive controller during different operating points.