Computational-Based Framework for Optimizing Dynamic Processes with Plant-Model Mismatch

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I. M. Mujtaba
M. A. Hussain

Abstract

A general computational sequence in optimizing the operation of a dynamic process is firstly highlighted in this paper. However, in most cases these dynamic processes include process-model mismatch, which shifts the optimal operation of the process. To overcome this, a model-mismatch estimator such as the neural network technique has been implemented in the optimization strategy. A modified general computational framework to incorporate these mismatches is developed for this purpose. The framework also allows the use of discrete process data in a continuous model to predict discrete and/or continuous mismatch profiles. The strategy is applied on a batch distillation system and the optimal operation using model mismatches is found to be comparable to that using the actual process model.

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How to Cite
Mujtaba, I. M., & Hussain, M. A. (2000). Computational-Based Framework for Optimizing Dynamic Processes with Plant-Model Mismatch. Malaysian Journal of Computer Science, 13(1), 27–33. Retrieved from https://malindojournal.um.edu.my/index.php/MJCS/article/view/5817
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