A servo system control with time-varying load using type-2 fuzzy neural system

Author

Oniz, Yesim ; Kayacan, Erdal ; Aras, Ayse Cisel ; Kaynak, Okyay ; Abiyev, Rahib

Author_Institution

Dept. of Electr. & Electron. Eng., Bogazici Univ., Istanbul, Turkey

fYear

2010

fDate

7-10 Nov. 2010

Firstpage

35

Lastpage

40

Abstract

A type-2 fuzzy neural system (T2FNS) is proposed in this paper for process control. The structure of the system is presented and the rules for updating its parameters are derived using the gradient algorithm. The effectiveness of the proposed approach is evaluated on a laboratory setup that regulates the speed of a DC motor and the experimental results are compared with those obtained with the use of a type-1 fuzzy neural system (T1FNS). It is seen that T2FNS results in reduced oscillations around the set point in the presence of load disturbances.

Keywords

DC motors; fuzzy systems; gradient methods; neural nets; process control; servomechanisms; time-varying systems; DC motor; gradient algorithm; load disturbance; process control; servo system control; time varying load; type-1 fuzzy neural system; type-2 fuzzy neural system; DC motors; Fuzzy sets; Fuzzy systems; Load modeling; Torque; Training; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society

Conference_Location

Glendale, AZ

ISSN

1553-572X

Print_ISBN

978-1-4244-5225-5

Electronic_ISBN

1553-572X

Type

conf

DOI

10.1109/IECON.2010.5675372

Filename

5675372