الفهرس 
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Abstract
Drying, especially rotary drying is one of the oldest and most common operation unit in industry. 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.
The aim of this research is to improve dryer performance by developing control systems based on modern adaptive control techniques. By introducing a dynamic model for the drying process, as the complexity and highly non-linear dynamics of this process make it difficult to model the dryer. A combination between two previously dynamic models of dryer plant using the drying rate equation, which causes the non-linearity of the model substituting in the general model equations. Then developing and applying control systems based on fuzzy logic controllers (FLC), developing control system as Variable Structure Controller (VSC) based on FLC, also developing control system depending on Adaptive Neuro-Fuzzy controller is introduced. Applying this suggested controller on the plant dryer will lead to reduce energy consuming. By reducing the fuel and air used by the dryer, the efficiency of the dryer also increases.
The comparison between these different control systems was carried out through simulations when a step change in the input moisture of solids occurs. The simulated parameters are based on the pilot plant dryer. The simulation results have been compared with the results achieved by the traditional PID-controller. The behavior of the suggested control systems has been tested with simulations based on the model of a plant dryer using Matlab®, Simulink, Fuzzy Logic Toolbox &ANFIS Toolbox.