DocumentCode :
2667677
Title :
A review of decoupling control based on multiple models
Author :
Liu, Guohai ; Wang, Zhaoxia ; Mei, Congli ; Ding, Yuhan
Author_Institution :
Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhenjiang, China
fYear :
2012
fDate :
23-25 May 2012
Firstpage :
1077
Lastpage :
1081
Abstract :
In this article, we review and discuss methods for decoupling control which include conventional decoupling and adaptive decoupling. Decoupling methods which is used to solve the multivariable coupled in nonlinear control are always a hot issue. The major algorithms such as neural network and fuzzy control are described in details and critically reviewed in this work. The advantages and disadvantages of these algorithms are analyzed. The review reveals the tremendous prospect of decoupling algorithms in nonlinear control. It is important to seek effective and simple decoupling methods.
Keywords :
adaptive systems; fuzzy control; multivariable control systems; neurocontrollers; nonlinear control systems; adaptive decoupling; decoupling algorithms; fuzzy control; multiple model; multivariable decoupling control; neural network; nonlinear control; Adaptation models; Adaptive systems; Control systems; Couplings; MIMO; Neural networks; Process control; adaptive decoupling control; fuzzy control; multivariable decoupling control; neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
Type :
conf
DOI :
10.1109/CCDC.2012.6244171
Filename :
6244171
Link To Document :
بازگشت