Nonlinear predictive control of a drying process using genetic algorithms.

ISA Trans

Department of Electronics and Telecommunications Engineering, Kocaeli University, 41040, Kocaeli, Turkey.

Published: October 2006

A nonlinear predictive control technique is developed to determine the optimal drying profile for a drying process. A complete nonlinear model of the baker's yeast drying process is used for predicting the future control actions. To minimize the difference between the model predictions and the desired trajectory throughout finite horizon, an objective function is described. The optimization problem is solved using a genetic algorithm due to the successful overconventional optimization techniques in the applications of the complex optimization problems. The control scheme comprises a drying process, a nonlinear prediction model, an optimizer, and a genetic search block. The nonlinear predictive control method proposed in this paper is applied to the baker's yeast drying process. The results show significant enhancement of the manufacturing quality, considerable decrease of the energy consumption and drying time, obtained by the proposed nonlinear predictive control.

Download full-text PDF

Source
http://dx.doi.org/10.1016/s0019-0578(07)60234-1DOI Listing

Publication Analysis

Top Keywords

drying process
20
nonlinear predictive
16
predictive control
16
baker's yeast
8
yeast drying
8
drying
7
nonlinear
6
control
6
process
5
control drying
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!