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Engineering industry controllers using neuroevolution

Published online by Cambridge University Press:  22 July 2005

NABIL M. HEWAHI
NABIL M. HEWAHI
Affiliation:
Computer Science Department, Islamic University of Gaza, Gaza, Palestine
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Abstract

Neuroevolution, or evolving neural networks with evolution algorithms such as genetic algorithms, is becoming one of the hottest areas in hybrid systems research. One of the areas that become under research using neuroevolutions is the controllers. In this paper, we shall present two engineering controllers based on neuroevolutions techniques. One of the controllers is used to monitor the temperature and humidity in an industry. This controller is having a linear behavior. The second controller is concerned with scheduling parts in queues in an industry. The scheduling controller is having a nonlinear behavior. The results obtained by the proposed controllers based on neuroevolution are compared with results obtained by traditional methods such as neural networks with backpropagation and ordinary simulation for the controller. The results show that the neuroevolution approaches outperform the results obtained by other methods.

Keywords

Control SystemsNeuroevolutionReal-Time Systems
Type
PRACTICUM PAPER
Information
AI EDAM , Volume 19 , Issue 1 , February 2005 , pp. 49 - 57
Copyright
2005 Cambridge University Press

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