Modelling of A Fluidized Bed Drier Using Artificial Neural Network |
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Authors: | A Balasubramanian RC panda VS Ramachandra Rao |
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Affiliation: | 1. Department of Chemical Engineering, Indian Institute of Technology , Madras, 600 036, India;2. Chemical Engineering Area, Central Leather Research Institute , Adyar, 600 020, Madras |
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Abstract: | ABSTRACT Proper modelling of a fluidized bed drier (FBD) is important to design model based control strategies. A FBD is a non-linear multivariable system with non-minimum 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” non-linearities, presents itself as a convenient tool for modelling such systems. In this work, an ANN model for continuous drying FBD is presented. A three layer fully connected feedfordward network with three inputs and two outputs is used. Backpropagation 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 behaviour of FBD adequately. |
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Keywords: | modelling fluidized bed drier artificial neural networks backpropagation |
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