Presenter Information

Matthew CmielFollow

Major

Computer Engineering

Anticipated Graduation Year

2020

Access Type

Open Access

Abstract

This project 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.

Faculty Mentors & Instructors

Dr. Brook Abegaz, Assistant Professor, Engineering Science

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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

This project 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.