Quality-based Control System for Corn Drying
Ralph Brown, PhD, PEng
Valerie Davidson, PhD, PEng
The objective of this research project is to investigate the relationships that exist among corn moisture content, drying air temperature, timing, and duration of exposure to drying air on stress cracking and milling quality (starch yield). To accomplish this goal, a fuzzy knowledge base is being developed from the relationships that will allow selection of an appropriate drying temperature and exposure time combination for minimization of grain damage in drying to a target moisture content (i.e., 15.5%). In addition, a control system is being created that uses the knowledge base in a feed-forward control situation, with feedback correction for final moisture content, to establish appropriate dryer control dryer settings. This control system will be tested for its' reliability and performance in an on-farm situation.
School of Engineering professors Ralph Brown and Valerie Davidson are using computer-based fuzzy mathematical principles to develop a system that will continuously monitor food grade corn as passes through the artificial drying process. The use of fuzzy logic based controllers will allow a quick and flexible response to the inherent variability of the corn being processed.