Neuro-controller design using genetic optimized pole placement method

Authors:
Cornel Rentea
Affiliations:
Department of Automation and Computer Science, University "Lucian Blaga" Sibiu, Sibiu, Romania
Venue:
ACMOS'05 Proceedings of the 7th WSEAS international conference on Automatic control, modeling and simulation
Year:
2005

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Abstract

In this paper, in order to improve the training of a neural controller implemented using a direct inverse scheme we use pole placement design enhanced with the help of a genetic algorithm. We discuss this optimization of training a neural network controller for the Inverted Pendulum problem, considered an acknowledged benchmark in nonlinear system control.