Modelling of a fluidized bed dryer using artificial neural network
- Indian Inst. of Tech., Madras (India). Dept. of Chemical Engineering
- Central Leather Research Inst., Madras (India). Chemical Engineering Area
Proper modelling of a fluidized bed dryer (FBD) is important to design model based control strategies. A FBD is a nonlinear multivariable system with nonminimum phase characteristics. Due to the complexities in FBD conventional Modelling techniques are cumbersome. Artificial neural network (ANN) with its inherent ability to learn and absorb nonlinearities, presents itself as a convenient tool for modelling such systems. In this work, an ANN model for a continuous drying FBD is presented. A three layer fully connected feedforward network with three inputs and two outputs is used. A back propagation learning algorithm is employed to train the network. The training data is obtained from computer simulation of a FBD model from published literature. The trained network is evaluated using randomly generated data as input and observed to predict the behavior of FBD adequately.
- Sponsoring Organization:
- USDOE
- OSTI ID:
- 378048
- Journal Information:
- Drying Technology, Vol. 14, Issue 7-8; Other Information: PBD: 1996
- Country of Publication:
- United States
- Language:
- English
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