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Application of neural network to hybrid systems with binary inputs

Holderbaum, W. (2007) Application of neural network to hybrid systems with binary inputs. IEEE Transactions on Neural Networks, 18 (4). pp. 1254-1261. ISSN 1045-9227

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To link to this article DOI: 10.1109/tnn.2007.899181

Abstract/Summary

Boolean input systems are in common used in the electric industry. Power supplies include such systems and the power converter represents these. For instance, in power electronics, the control variable are the switching ON and OFF of components as thyristors or transistors. The purpose of this paper is to use neural network (NN) to control continuous systems with Boolean inputs. This method is based on classification of system variations associated with input configurations. The classical supervised backpropagation algorithm is used to train the networks. The training of the artificial neural network and the control of Boolean input systems are presented. The design procedure of control systems is implemented on a nonlinear system. We apply those results to control an electrical system composed of an induction machine and its power converter.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Systems Engineering
ID Code:15263
Uncontrolled Keywords:Boolean control, linear system, neural network (NN)

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