Design of a neuro-fuzzy controller for speed control applied to AC servo motor

Author

Kim, Sang Hoon ; Kim, Lark Kyo

Author_Institution

Dept. of Electr. Eng., Konkuk Univ., South Korea

Volume

1

fYear

2001

fDate

2001

Firstpage

435

Abstract

In this study, a neuro-fuzzy controller which has the characteristic of fuzzy control and an artificial neural network is designed. A fuzzy rule to be applied is automatically selected by the allocated neurons. The neurons correspond to fuzzy rules that are created by an expert. To adapt the more precise modeling, error backpropagation learning of adjusting the link-weight of fuzzy membership function in the Neuro-Fuzzy controller is implemented. The more classified fuzzy rule is used to include the property of the dual mode method. In order to verify the effectiveness of the algorithm designed above, an operating characteristic of an AC servomotor with variable load is investigated

Keywords

AC motors; backpropagation; control system analysis; control system synthesis; fuzzy control; fuzzy neural nets; machine control; machine theory; neurocontrollers; servomotors; velocity control; AC servomotor; allocated neurons; control simulation; dual mode method; error backpropagation learning; fuzzy membership function link-weight adjustment; fuzzy rule selection; neuro-fuzzy speed controller design; operating characteristic; AC motors; Automatic control; Control systems; Fuzzy control; Fuzzy systems; Neural networks; Neurons; Servomechanisms; Servomotors; Velocity control;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics, 2001. Proceedings. ISIE 2001. IEEE International Symposium on

Conference_Location

Pusan

Print_ISBN

0-7803-7090-2

Type

conf

DOI

10.1109/ISIE.2001.931829

Filename

931829