DocumentCode
2675714
Title
BP neural network control for a class of nonlinear systems
Author
Liang Zhiwei ; Su Luyan ; Zhu Songhao ; Fang, Fang
Author_Institution
Coll. of Autom., Nanjing Univ. of Posts & Telecommun., Nanjing, China
fYear
2012
fDate
23-25 May 2012
Firstpage
3865
Lastpage
3869
Abstract
A method based on BP neural network is proposed for a class of nonlinear SISO systems. It fits the nonlinear part of the system by learning the weight coefficients of the network on-line, designs the control rules to linearize the system, and assure the global stability. In this paper, the method is popularized in the MIMO systems. Experimental Results of two examples demonstrate the performance of our approach .
Keywords
MIMO systems; backpropagation; control system synthesis; learning (artificial intelligence); neurocontrollers; nonlinear control systems; stability; BP neural network control; MIMO systems; control rules designs; global stability; nonlinear SISO systems; online learning; system linearization; weight coefficients; Automation; Educational institutions; Electronic mail; MIMO; Neural networks; Nonlinear systems; Telecommunications; BP neural network; linearization; nonlinear systems; on-line learning;
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.2012.6244619
Filename
6244619
Link To Document