DocumentCode
3493733
Title
Controller design using parametric neural networks
Author
HashemiNejad, M. ; Murata, J. ; Hirasawa, K.
Author_Institution
Dept. of Electr. Eng., Kyushu Univ., Fukuoka, Japan
fYear
1995
fDate
26-28 Jul 1995
Firstpage
1275
Lastpage
1280
Abstract
A neural network (NN) of a more flexible internal structure than usual is used to design a better controller. A parametric NN (PNN) can represent both linear and nonlinear relationships explicitly and simultaneously by setting its parameters appropriately. In many cases we have some information about the system which enable us to build a linear controller for it. But of course this is not enough for treating nonlinear plants. Using PNN we could make a complimentary linearized controller and then, after starting the learning, in an online manner it will be extended to a nonlinear dominant controller
Keywords
control system synthesis; neurocontrollers; nonlinear control systems; complimentary linearized controller; controller design; flexible internal structure; nonlinear dominant controller; parametric neural networks; Artificial intelligence; Control systems; Control theory; Electrical equipment industry; Error correction; Linear systems; Neural networks; Nonlinear control systems; Nonlinear equations; Nonlinear systems;
fLanguage
English
Publisher
ieee
Conference_Titel
SICE '95. Proceedings of the 34th SICE Annual Conference. International Session Papers
Conference_Location
Hokkaido
Print_ISBN
0-7803-2781-0
Type
conf
DOI
10.1109/SICE.1995.526694
Filename
526694
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