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Optimization of a neural architecture for the direct control of a Boost converter

Author(s): Fredy Hernán Martinez Sarmiento | Diego Fernando Gomez Molano | Mariela Castiblanco Ortiz

Journal: Tecnura
ISSN 0123-921X

Volume: 16;
Issue: 32;
Start page: 41;
Date: 2012;
Original page

Keywords: control | DC/DC conversion | intelligent systems | power

In research related to control of DC/DC converters, artificial intelligence techniques are a great improvement in the design and performance. However, some of these tools require the use of trial and error strategies in the design, making it difficult to obtain an optimal structure. In this paper, we propose a direct control based on artificial neural network, whose design has been optimized using bio-inspired searching strategies, with the idea of optimizing simultaneously two different but important aspects of the network: architecture and weights connections. The control was successfully applied to a boost type converter. The results obtained allow us to observe the dynamic performance of the scheme, in which the response time and variation in the output voltage can be concluded that the criteria used for the control loop design were appropriate.

Tango Jona
Tangokurs Rapperswil-Jona

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