STATE ESTIMATION IN THE BATCH DRYING OF FOODS

Measurement of material moisture content is necessary for the control of product quality in batch drying. However, this variable cannot be m easured on-line, and state estimation techniques are proposed. A non-l inear dynamic model is developed for batch drying of foods. Process di sturbances and measurement errors are modeled as stochastic processes and a hybrid extended Kalman filter is employed for state estimation. This filter is based on the local linearization of the process model a round the suboptimal filter estimates. The moisture estimation approac h was applied to experimental points obtained in a laboratory dryer wi th quite satisfactory results.