OPTIMIZATION OF PROCESS CONTROL IN DRY SUGAR BEET PULP PRODUCTION

In this paper, a neuro-fuzzy control system has been presented to be an aid in prospective development of novel rotary drying supervisory control for sugar beet dry pulp production. Drying is common process in most of production industries, especially in food preparation and production. Sugar beet dry pulp is used as highly protein rich cattle food and can also be used as alternative source of cellulose for paper industry or as fuel for biomass fired boilers. Co-current direct rotary drying of such product is highly difficult to control due to its parameters nonlinearities and long lag times. Thus, this proposed model tries to overcome unavailability of real mathematical model and imperfection of data collected by used sensors.