pH control in biological process using MMPC based on neuro-fuzzy model by LOLIMOT algorithm

Saadat, Ali; Alvanagh, Ahmad Akbari; Rezaei, Hamed

doi:10.1109/ascc.2013.6606384

2013 9th Asian Control Conference (ASCC) 2013

DOI: 10.1109/ascc.2013.6606384

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pH control in biological process using MMPC based on neuro-fuzzy model by LOLIMOT algorithm

Ali Saadat

Ahmad Akbari Alvanagh

Hamed Rezaei

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2015

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Model predictive control of pH neutralization processes: A review

Hermansson

Syafiie

2015

Control Engineering Practice

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The paper provides a review of the different approaches of Model Predictive Control (MPC) to deal with the nonlinearities and transient behavior associated with pH and its control. Firstly a description of the pH system and what makes it difficult to control is presented, followed by the general description of the structure of MPC. The different applications of MPC vary mostly in the way the model is described and how the optimization is carried out to obtain the desired control action. The different modeling techniques applied to the MPC, which is used to describe the behavior of the pH are ranging from simple linear models, multiple linear models like piecewise linear descriptions and fuzzy models, to nonlinear descriptions like Wiener models and the use of artificial neural networks. The models and their respective ways of application are reviewed. Finally, the areas where more research is needed are addressed.

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Model predictive control of pH neutralization processes: A review

Hermansson

Syafiie

2015

Control Engineering Practice

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pH control in biological process using MMPC based on neuro-fuzzy model by LOLIMOT algorithm

Cited by 1 publication

References 12 publications

Model predictive control of pH neutralization processes: A review

Model predictive control of pH neutralization processes: A review

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