Title :
Deabbeat discrete control throgh of the identification with neural networks for presure system
Author :
Pezzotti, G. ; Valencia, Juan ; Londono, N.
Author_Institution :
Nat. Res. Council & Biosensing Technol., Italy
fDate :
6/1/2012 12:00:00 AM
Abstract :
This paper, is an application in the area of automatic control with artificial neural networks, for control of the pressure of a tank in the ethanol plant; with an algorithm deadbeat; with previously is realized calculus of coefficients of the neural network in method off line. The weights was calculates for the network backprogation, are explained the proceedings for the net and algorithm control, the results of real time control; the calculus of coefficient of net is realized with Matlab and control in C++. This technical of control utilizing neural networks is a good help instrument for resolved the problems of stabilizing and velocity.
Keywords :
backpropagation; discrete systems; industrial control; industrial plants; neural nets; pressure control; process control; tanks (containers); C++; Matlab; automatic control; discrete deadbeat control; ethanol plant; identification; network backprogation; neural networks; plant pressure control; real time control; Adaptation models; Backpropagation; Biological neural networks; MATLAB; Mathematical model; Process control; Robustness; Deabbeat control; Industrial control; Neural networks; backpropagation;
Journal_Title :
Latin America Transactions, IEEE (Revista IEEE America Latina)
DOI :
10.1109/TLA.2012.6272481