ABSTRACT
Today, most industrial dryers are equipped with varying levels of automatic controllers. Often they use simple control strategies based, for example, simply on the exhaustgas temperature for a direct dryer. Small-scale and slow drying operations are often controlled (or adjusted for process upsets) manually. Very high production units, those involving very rapid drying or units that produce products within stringent quality specications, must be equipped with some degree of automatic control. Although commercial dryers currently use conventional control strategies, it is expected that within the next decade more and more industrial dryers will utilize model-based control (MBC), fuzzy logic control (FLC), or neural nets control when the dryer performance is highly nonlinear and difcult to predict with simple mathematical models. Some improvements in dryer controls became available because of the development of better sensors and analyzers, whereas others are by-products of new, more sophisticated, computer-based control techniques [1]. This chapter provides an introductory overview of both the conventional and the emerging control schemes
for industrial drying. Examples are cited with reference to the more common dryers (e.g., spray, ¤ash, ¤uid-bed dryers). Relevant information is also provided to the readers interested in intelligent control systems based on expert systems, fuzzy logic, or neural nets. It is inconceivable that within this decade equipment suppliers will market “smart” dryers that can adjust their operating parameters consistent with the needs of product quality during drying. However, such a possibility exists for some dryer types in a longer term.
