Abstract
Practical implementations of two typical types of artificial neural networks (ANNs), feedforward networks and external recurrent networks, as the model for model predictive control (MPC) were performed on the dual temperature control problem of two distillation columns, a pilot scale i-butane and n-butane distillation column and a bench scale ethanol and water column. The superiority of MPC based on an ANN models over conventional proportional-integral controllers and over dynamic matrix control were testified through experiments.
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Chu, JZ. et al. (2003). An Experimental Study of Model Predictive Control Based on Artificial Neural Networks. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_175
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DOI: https://doi.org/10.1007/978-3-540-45224-9_175
Publisher Name: Springer, Berlin, Heidelberg
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