By Topic

Applications of a model based predictive control to heat-exchangers

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Balan, R. ; Tech. Univ. of Cluj-Napoca, Cluj-Napoca ; Maties, V. ; Hodor, V. ; Hancu, O.
more authors

Model based predictive control (MBPC) is an optimization-based approach that has been successfully applied to a wide variety of control problems. When MBPC is employed on nonlinear processes, the application of this typical linear controller is limited to relatively small operating regions. The accuracy of the model has significant effect on the performance of the closed loop system. Hence, the capabilities of MBPC will degrade as the operating level moves away from its original design level of operation. This paper presents an MPC algorithm which uses on-line simulation and rule-based control. The basic idea is the online simulation of the future behaviour of control system, by using a few control sequences and based on nonlinear analytical model equations. Finally, the simulations are used to obtain the 'optimal' control signal. These issues will be discussed and nonlinear modeling and control of a single-pass, concentric-tube, counter flow or parallel flow heat exchanger w ill be presented as an example.

Published in:

Control & Automation, 2007. MED '07. Mediterranean Conference on

Date of Conference:

27-29 June 2007