Optimal Self Tuning Neural Network Controller Design
نویسندگان
چکیده
The proposed paper deals with modeling and control of continuous-time processes using artificial neural network with orthogonal activation functions, applicable for real-time control. A genetic algorithm has been used to find the optimal neural structure for on-line identification with the best learning algorithm. A moving prediction horizon in the control algorithm found by genetic algorithm has been compared with a constant prediction horizon. The proposed algorithms were verified on practical control problem and have proved a good performance. Copyright © 2005 IFAC
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تاریخ انتشار 2005