Abstract
Drying is a very complex non-linear process including the movement of solids in addition to the thermal drying. This means that both the modeling and control of a rotary dryer is difficult with conventional methods, and most of previous researches goes to directly linearize the non-linear model, estimating many parameters that affect the model or work on specific linear model so applying modern controllers even fuzzy or Neuro-Fuzzy always gives approximate results and valid only in certain operating points, in this paper we try to make a combination between two dynamic models of dryer plant to solve the drying rate equation which mainly causes the non-linearity of the model. This article will validate the proposed model then applying modern adaptive control techniques Fuzzy and Neuro-Fuzzy controllers, comparing the behavior of the plant dryer when connected to each of this controllers versus the conventional PID , the aim is to improve dryer control, this will lead to energy, cost savings and increasing efficiency of the drying, the behavior of the control systems has been tested with simulations based on the model of a plant dryer using The Matlab®, and Simulink and Fuzzy Logic Toolbox, ANFIS Toolbox.
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