Control system using fuzzified input neural network

Author

Treesatayapun, C. ; Uatrongjit, S. ; Likit-Anurucks, K. ; Kantapanit, K.

Author_Institution

Dept. of Electr. Eng., Chiang Mai Univ., Chiangmai, Thailand

Volume

2

fYear

2002

fDate

2002

Firstpage

163

Abstract

In this paper, a new fuzzy neural network structure called the fuzzified input neural network (FINN) is presented. The FINN structure is derived based on human knowledge in the form of fuzzy if-then rules. The initial setting of its parameters can be chosen intuitively from expert experience. These parameters are then adaptively adjusted during system operation. Comparisons between the proposed network and the conventional Mamdani fuzzy inference are described. The performance of FINN is demonstrated by using it as the controller for the single inverted pendulum plant. Some simulation results are given.

Keywords

adaptive control; fuzzy control; fuzzy neural nets; inference mechanisms; neurocontrollers; nonlinear control systems; pendulums; FINN; Mamdani fuzzy inference; RBF network; adaptive control; adaptively adjusted parameters; control system; fuzzified input neural network; fuzzy if-then rules; fuzzy neural network structure; human knowledge; initial parameter setting; simulation; single inverted pendulum plant controller; system operation; Adaptive control; Control systems; Electronic mail; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Humans; Neural networks; Radial basis function networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2002. APCCAS '02. 2002 Asia-Pacific Conference on

Print_ISBN

0-7803-7690-0

Type

conf

DOI

10.1109/APCCAS.2002.1115145

Filename

1115145