DocumentCode :
2495569
Title :
Nonlinear adaptive control using a fuzzy switching mechanism based on improved quasi-ARX neural network
Author :
Wang, Lan ; Cheng, Yu ; Hu, Jinglu
Author_Institution :
Grad. Sch. of Inf., Production & Syst., Waseda Univ., Kitakyushu, Japan
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
7
Abstract :
This paper presents a novel approach for designing adaptive controller of nonlinear dynamical systems based on an improved quasi-ARX neural network prediction model. The improved quasi-ARX neural network prediction model has two parts: the linear part is used for stability and the nonlinear part is used to satisfy accuracy requirement. Then, we can obtain a linear controller and a nonlinear controller based on the characteristic of the improved quasi-ARX neural network prediction model. A fuzzy switching algorithm is designed between the two controllers. Theory analysis and simulations are given to show the effectiveness of the proposed method both on stability and accuracy.
Keywords :
adaptive control; control system synthesis; fuzzy control; linear systems; neural nets; nonlinear control systems; nonlinear dynamical systems; stability; switching; controller design; fuzzy switching mechanism; linear controller; nonlinear adaptive control; nonlinear dynamical system; quasiARX neural network prediction model; stability; Adaptation model; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
ISSN :
1098-7576
Print_ISBN :
978-1-4244-6916-1
Type :
conf
DOI :
10.1109/IJCNN.2010.5596819
Filename :
5596819
Link To Document :
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