Neural-Genetic Control Algorithm of Nonlinear Systems.

Autor: Kajan, Slavomír, Dideková, Zuzana, Kozák, Stefan, Linder, Marek
Předmět:
Zdroj: International Review of Automatic Control; Mar2013, Vol. 6 Issue 2, p206-210, 5p, 4 Diagrams, 4 Charts, 10 Graphs
Abstrakt: Control of nonlinear systems is a challenging task. One of the ways of control of such systems is the use of neural networks as controllers. In this paper a methodology is proposed, where for neural controller design the genetic algorithm has been used. This method allows find optimal adjustment of neural network weights so that high performance is obtained. The proposed control method is realized in Matlab/Simulink and demonstrated on two examples of nonlinear dynamical systems. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index