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http://dx.doi.org/10.5762/KAIS.2013.14.12.6484

Direct Controller for Nonlinear System Using a Neural Network  

Bae, Ceol-Soo (Information and Communication Engineering, Kwandong University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.14, no.12, 2013 , pp. 6484-6487 More about this Journal
Abstract
This paper reports the direct controller for nonlinear plants using a neural network. The controller was composed of an approximate controller and a neural network auxiliary controller. The approximate controller provides rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not place too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network was trained and the system showed stable performance for the inputs it has been trained for. The simulation results showed that it was quite effective and could realize satisfactory control of the nonlinear system.
Keywords
complementary signal; direct controller; neural network; nonlinear system; RBF;
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