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Ukraine is an energy-dependent country and directing its efforts into economical use of its own energy resources. One relevant available energy source is peat briquette. During its production it is necessary not only to improve the quality of briquettes, but also to reduce the total expenses of energy required for their production, particularly in the drying process. For this, a mathematical model of peat drying is developed using the GMDH (Group Method of Data Handle). Next, with measured disturbances, optimal input variables for the drying process are found using mathematical optimization and ANN (artificial neural network). To avoid fast changing of the operational conditions while avoiding over drying or under drying of the peat, the operational conditions are classified into a number of classes. Finally, an iterative procedure for changing the input parameters from the past values to new values is introduced to ensure improved

Optimal Operation of the Peat Drying Process in Steam Tube Dryers