Design of neuro-fuzzy controller for the speed control of a DC servo motor

Author

Kang, Young-Ho ; Kim, Lark-Kyo

Author_Institution

Kon-Kuk Univ., Seoul, South Korea

Volume

2

fYear

2001

fDate

37104

Firstpage

731

Abstract

The authors have designed a neuro-fuzzy controller to improve some problems that occur when the nonlinear system is controlled by a fuzzy logic controller. Their model obtains fast-time response, maximized learning effect and shortened settling time. To prove the capability of the neuro-fuzzy controller designed in this paper, this neuro-fuzzy model is applied to a DC servomotor. As a result, this controller does not produce overshoot, which occurs in the PID controller, and also does not produce the steady state error of FLC. Also, it shortens the settling time by about 10%. In addition, the authors are aware that their model has only about 60% of the value of current peak of the PID controller

Keywords

DC motors; control system analysis; control system synthesis; fuzzy control; fuzzy neural nets; learning (artificial intelligence); machine control; machine theory; neurocontrollers; servomotors; velocity control; DC servomotor; control design; control simulation; fast-time response; fuzzy logic controller; maximized learning effect; neuro-fuzzy speed controller design; settling time; steady state error; Control systems; DC motors; Error correction; Fuzzy control; Neural networks; Servomechanisms; Servomotors; Steady-state; Three-term control; Velocity control;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Machines and Systems, 2001. ICEMS 2001. Proceedings of the Fifth International Conference on

Conference_Location

Shenyang

Print_ISBN

7-5062-5115-9

Type

conf

DOI

10.1109/ICEMS.2001.971780

Filename

971780