Computerised constant tension control for a film metal coating machine with artificial neural network algorithm

Author

Luo, Fang Lin

Author_Institution

Nanyang Technol. Inst., Singapore

Volume

1

fYear

1997

fDate

26-29 May 1997

Firstpage

455

Abstract

An artificial neural network algorithm is a good control method to solve problems for static and linear control systems. This technique has been quickly developed worldwide. This paper introduces a new method namely multiple page mapping backpropagation neural network (BPNN) algorithm. Using this method successfully solves the problems for quasi-static and nonlinear control systems. As an example, constant tension control for a film metal coating machine that is a system with multiple closed-loops, and multiple input and output variables, was investigated. Desired speed and tension responses are achieved by implementing BPNN to this machine. Satisfactory experimental results are obtained

Keywords

DC motors; angular velocity control; backpropagation; closed loop systems; coating techniques; electric current control; machine control; nonlinear control systems; power engineering computing; DC motor; artificial neural network algorithm; computerised constant tension control; film metal coating machine; linear control system; multiple closed-loops; multiple input variables; multiple output variables; multiple page mapping backpropagation neural network; nonlinear control system; speed response; static control system; tension response; Artificial neural networks; Circuits; Coatings; Control systems; DC motors; Interference; Nonlinear control systems; Proportional control; Torque control; Velocity control;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Electronics and Drive Systems, 1997. Proceedings., 1997 International Conference on

Print_ISBN

0-7803-3773-5

Type

conf

DOI

10.1109/PEDS.1997.618747

Filename

618747