Smart Control of Buck Converters using a Switching-based Clustering Algorithm

This paper proposes a new approach to the control of switching voltage regulators (buck converters). The method is performed using a switching-based clustering algorithm. The implementations of competing approaches such as a fuzzy-logic controller, proportional integral derivative controller and a n...

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Veröffentlicht in:2019 14th Annual Conference System of Systems Engineering (SoSE) S. 334 - 339
Hauptverfasser: Abegaz, B.W., Cmiel, M.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.05.2019
Schlagworte:
Buck converters
clustering
Clustering algorithms
Control systems
Machine learning
Multilevel converters
Neural networks
power converters
Regulators
Switches
switching
System of systems
unsupervised machine learning
Voltage control
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Zusammenfassung:This paper proposes a new approach to the control of switching voltage regulators (buck converters). The method is performed using a switching-based clustering algorithm. The implementations of competing approaches such as a fuzzy-logic controller, proportional integral derivative controller and a neural network based controller are presented in order to compare and evaluate the performance of the switching-based clustering algorithm. The results of the approach show that the proposed method could improve the stability and the performance of the buck converter system by 2.7% in terms of settling time and by 0.6% in terms of the overshoot value as compared to other control methods for buck converters.
DOI:10.1109/SYSOSE.2019.8753864