Neural Network Predictive Control of a Chemical Reactor

Vasičkaninová, Anna and Bakošová, Monika Neural Network Predictive Control of a Chemical Reactor Acta Chimica Slovaca, Vol.2, No. 2, 2009, 21-36

Document type: Článok z časopisu / Journal Article
Collection: Acta Chimica Slovaca  
 
Attached Files
Name Description MIMEType Size Downloads
acs_0044.pdf   acs_0044.pdf application/pdf 224.48KB 0

Author(s) Vasičkaninová, Anna
Bakošová, Monika
Title Neural Network Predictive Control of a Chemical Reactor
Journal name Acta Chimica Slovaca
Publication date 2009
Year available 2009
Volume number 2
Issue number 2
ISSN 1337-978X
Start page 21
End page 36
Total pages 16
Place of publication Bratislava
Publisher Slovak Technical University
Collection year 2009
Language english
Subject 290000 Engineering and Technology
290600 Chemical Engineering
290602 Process Control and Simulation
Abstract/Summary Model Predictive Control (MPC) refers to a class of algorithms that compute a sequence of manipulated variable adjustments in order to optimize the future behaviour of a plant. MPC technology can now be found in a wide variety of application areas. The neural network predictive controller that is discussed in this paper uses a neural network model of a nonlinear plant to predict future plant performance. The controller calculates the control input that will optimize plant performance over a specified future time horizon. In the paper, simulation of the neural network based predictive control of the continuous stirred tank reactor is presented. The simulation results are compared with fuzzy and PID control.
Keyword(s) model predictive control
fuzzy control
PID control
neural network
continuous stirred tank reactor
 
 
User Comments
 
Access Statistics: 0 Abstract Views, 0 File Downloads Detailed Statistics
Created: Fri, 18 Dec 2009, 13:36:57 CET by Iveta Drtilová . Detailed History