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J. Madar, J. Abonyi and F. Szeifert, “Feedback Linearizing Control Using Hybrid Neural Networks Identified by Sensitivity Approach,” Engineering Application of Artificial Intelligence, Vol. 18, No. 3, 2005, pp. 335-343. doi:10.1016/j.engappai.2004.09.006

has been cited by the following article:

• TITLE: Energy Efficiency Improvement of an Industrial Crystallization Process Using Linearizing Control

  AUTHORS: Cédric Damour, Michel Benne, Lionel Boillereaux, Brigitte Grondin-Perez, Jean-Pierre Chabriat

  KEYWORDS: Energy Efficiency Improvement; Linearizing Control; Industrial Control; Phase Changing; Crystallization

  JOURNAL NAME: Journal of Crystallization Process and Technology, Vol.2 No.2, April 24, 2012

  ABSTRACT: This paper illustrates the benefits of a multivariable linearizing control approach applied to an industrial crystallization process. This relevant approach is declined according to two different strategies: first, a setpoint tracking is proposed for the couple crystal mass/concentration, whereas a second way consists in tracking of crystal content and concentration. The controlled variables, unavailable online, are issued from an observer developed in previous works. The performance of these strategies, which application to cane sugar crystallization constitutes a real novelty, are compared with experimental data issued from a PID-controlled industrial plant. The results reveal a significant improvement of energy efficiency, leading to an economy of more than 10% of energy.