DocumentCode :
2022428
Title :
Dynamic Decoupling of the MIMO System Based on the Elman Net
Author :
Li, Xinli ; Bai, Yan ; Zhang, Keming
Author_Institution :
Dept. of Autom., North China Electr. Power Univ., Beijing
Volume :
1
fYear :
2008
fDate :
17-18 Oct. 2008
Firstpage :
537
Lastpage :
540
Abstract :
Elman net is a kind of well-known recurrent neural networks. Because the original Elman net and modified Elman net can approach the dynamic system, it can be used to complete dynamic decoupling in the MIMO system. The online decoupling algorithm of nonlinear MIMO system based on the Elman net is proposed. As the target function of the Elman net, the generalized cross-correlation function is defined which can implement the online dynamic decoupling. The hybrid genetic algorithm is used to train the Elman net in order to compensate coupling effect. The effectiveness of the algorithm has been shown by numerical simulations combing nonlinear MIMO system.
Keywords :
MIMO systems; genetic algorithms; recurrent neural nets; Elman net; MIMO system; dynamic decoupling; generalized cross-correlation function; genetic algorithm; recurrent neural networks; Automation; Computational intelligence; Control systems; MIMO; Mathematics; Neural networks; Neurons; Nonlinear dynamical systems; Physics; Recurrent neural networks; Dynamic online decoupling; Elman net; Hybrid genetic algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3311-7
Type :
conf
DOI :
10.1109/ISCID.2008.181
Filename :
4725667
Link To Document :
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