DC Motor neuro-fuzzy controller using PSO identification

Author

Farid, Amro M. ; Barakati, S. Masoud

Author_Institution

Sch. of Electr. & Comput. Eng., Univ. of Sistan & Baluchestan, Zahedan, Iran

fYear

2014

fDate

20-22 May 2014

Firstpage

1162

Lastpage

1167

Abstract

DC Motor controller is the most important issue in many applications. There are trade-off between the performance and the final cost. Most of the proposed controllers in the territory of artificial intelligence have complicated computations that make them inapplicable. In this paper particle swarm optimization is used for identification of the DC motor and then adaptive neuro-fuzzy inference system is applied while it trained off-line by PSO. The proposed controller has been implemented in AVR´s ATMEGA32 microcontroller.

Keywords

DC motors; control engineering computing; finite element analysis; fuzzy control; fuzzy reasoning; machine control; microcontrollers; neurocontrollers; particle swarm optimisation; AVR ATMEGA32 microcontroller; DC motor PSO identification; DC motor neurofuzzy controller; adaptive neurofuzzy inference system; artificial intelligence; particle swarm optimization; Computers; DC motors; Educational institutions; Mathematical model; Microcontrollers; Permanent magnet motors; Pulse width modulation; ANFIS; ATMEGA32; AVR microprocessor; DC motor; PSO identification; PWM control;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering (ICEE), 2014 22nd Iranian Conference on

Conference_Location

Tehran

Type

conf

DOI

10.1109/IranianCEE.2014.6999711

Filename

6999711