Improving of Crystal Size Distribution Control Based on Neural Network-Based Hybrid Model for Purified Terephthalic Acid Batch Crystallizer

Authors

  • Paisan Kittisupakorn Chulalongkorn University
  • Preeya Somsong Chulalongkorn University
  • Mohd Azlan Hussain University of Malaya
  • Wachira Daosud Burapha University

DOI:

https://doi.org/10.4186/ej.2017.21.7.319

Abstract

A main difficult task in batch crystallization is to control the size distribution of crystal products. Complexity and highly nonlinear dynamic behavior directly affect to model-based control strategies which heavily depend on the rigorous knowledge of crystallization. In this work, neural network-based model predictive control and inverse neural network control strategies are proposed and integrated with an optimization based on neural network-based hybrid model to control temperatures of a purified terephthalic acid batch crystallizer. A neural network-based hybrid model of the batch crystallizer is developed to provide nonlinear dynamic responses used in optimization algorithm for finding an optimal temperature profile related to the quality of a crystal product. Then, the obtained optimal profile is used as set points of the proposed control strategies for improving the crystal product quality. The performances and robustness of the proposed controllers are evaluated in several cases such as for set point tracking and plant/model mismatches. Simulation results show that the neural network-based model predictive control gives the best control performance among the inverse neural network control and a conventional PID controller in all cases.

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Author Biographies

Paisan Kittisupakorn

Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand

Preeya Somsong

Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand

Mohd Azlan Hussain

Chemical Engineering Department, University of Malaya, Kuala Lumpur 50603, Malaysia

Wachira Daosud

Department of Chemical Engineering, Faculty of Engineering, Burapha University, Chonburi 20131, Thailand

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Published In
Vol 21 No 7, Dec 29, 2017
How to Cite
[1]
P. Kittisupakorn, P. Somsong, M. A. Hussain, and W. Daosud, “Improving of Crystal Size Distribution Control Based on Neural Network-Based Hybrid Model for Purified Terephthalic Acid Batch Crystallizer”, Eng. J., vol. 21, no. 7, pp. 319-331, Dec. 2017.