Comparative analysis of neural and P-I controller for

Author

Nagarajan, V.S. ; Balaji, M. ; Kamaraj, V. ; Seetha, B.

Author_Institution

Dept. of EEE, SSNCE, Chennai, India

fYear

2014

fDate

7-9 Jan. 2014

Firstpage

126

Lastpage

131

Abstract

This paper describes Artificial Neural Network (ANN) based speed and current controller design for Permanent Magnet Synchronous Motor (PMSM).The neural network controllers are designed to translate the speed and current errors into respective driving voltage signals to the input of PMSM. A multilayer feed forward neural network is trained using Back propagation learning algorithm to estimate the driving voltage input of PMSM. To analyze the performance of neural controller, the overall system is simulated under various operating conditions. The simulation results compared with conventional P-I controller for different conditions highlight the performance of the proposed controller in steady state and transient conditions.

Keywords

PI control; backpropagation; control engineering computing; electric current control; feedforward neural nets; machine control; permanent magnet motors; power engineering computing; synchronous motor drives; velocity control; ANN controller; PI controller; PMSM drive; artificial neural network controller; backpropagation learning algorithm; comparative analysis; current error controller design; driving voltage signal estimation; multilayer feed forward neural network; performance analysis; permanent magnet synchronous motor; speed error controller design; steady state conditions; transient conditions; Conferences; Decision support systems; Yttrium; ANN; Back propagation; P-I controller; PMSM;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Energy Systems (ICEES), 2014 IEEE 2nd International Conference on

Conference_Location

Chennai

Print_ISBN

978-1-4799-3738-7

Type

conf

DOI

10.1109/ICEES.2014.6924154

Filename

6924154