Automatic control of the crossflow microfiltration process using fuzzy logic

doi:10.1016/0376-7388(96)00027-0

Journal of Membrane Science

Volume 116, Issue 1, 24 July 1996, Pages 93-105

https://doi.org/10.1016/0376-7388(96)00027-0 Get rights and content

Abstract

In this paper, a study on dynamic control of crossflow filtration process using a fuzzy controller is proposed. The filtration is carried out on a microfiltration membrane for raw cane sugar syrup. Automatic control using a fuzzy controller which allows a simultaneous gradual action on the transmembrane pressure and crossflow velocity so as to maintain a constant permeate flux is developed. The results obtained show the best performance of this control strategy compared with constant operating conditions control during filtration (the quantity of permeate is multiplied by about two). The methodology to elaborate the fuzzy controller and the robustness of the controller are also discussed in this paper.

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Cited by (4)

Advanced control of membrane fouling in filtration systems using artificial intelligence and machine learning techniques: A critical review
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Citation Excerpt :
Defuzzification is the last step of the fuzzy system to obtain a final crisp output and is performed according to the MFs of the output variable. FL has been applied in several studies to model membrane fouling and also to develop automated systems for the better control and management of membrane fouling (Perrot et al., 1996; Sargolzaei et al., 2008). Table 2 represents a summary of studies that applied various inference systems and architectures to better control and monitor membrane fouling in different filtration processes.
This paper critically reviews all artificial intelligence (AI) and machine learning (ML) techniques for the better control of membrane fouling in filtration processes, with the focus on water and wastewater treatment systems. Artificial neural networks (ANNs), fuzzy logic, genetic programming and model trees were found to be four successfully employed modeling techniques. The results show that well-known ANNs such as multilayer perceptron and radial basis function can predict membrane fouling with an R² equal to 0.99 and an error approaching zero. Genetic algorithm (GA) and particle swarm optimization (PSO) are optimization methods successfully applied to optimize parameters related to membrane fouling. These optimization techniques indicated high capabilities in tuning various parameters such as transmembrane pressure, crossflow velocity, feed temperature, and feed pH. The results of this survey demonstrate that hybrid intelligent models utilizing intelligent optimization methods such as GA and PSO for adjusting their weights and functions perform better than single models. Clustering analysis, image recognition, and feature selection are other employed intelligent techniques with positive role in the control of membrane fouling. The application of AI and ML techniques in an advanced control system can reduce the costs of treatment by monitoring of membrane fouling, and taking the best action when necessary.
Prediction of specific permeate flux during crossflow microfiltration of polydispersed colloidal suspensions by fuzzy logic models
2010, Desalination
Fuzzy logic models for time-variant specific fluxes during crossflow microfiltration of several feed suspensions under a wide range of hydrodynamic parameters were derived and validated. The coefficient of efficiency values, which quantifies the degree of agreement between experimental observations and numerically calculated values were found greater than 0.96 for all cases. An important contribution of this research is that it is demonstrated that a single robust fuzzy model can quantitatively capture cumulative effects of a range of particle sizes on membrane fouling. Hence, empirical models incorporating fuzzy logical operators appear to encompass overall effects of non-linear colloidal transport and deposition mechanisms as well as changes in cake morphology and resistance with hydrodynamics better than mathematically complicated mechanistic models. This also suggests the use of fuzzy logic algorithms in programmable control systems for improved on-site operation of membrane-based liquid–solid separation employed in municipalities and industries.
Influence of operating parameters on separation of green syrup colored matter from sugar beet by ultra-and nanofiltration
2005, Journal of Food Engineering
The interest in membrane filtration in the sugar industry has recently increased. In sugar beet processing, the main problem is the separation of non-sucrose compounds, especially of colored matter. Separation of colored matter from green syrup was examined by ultra- and nanofiltration of a solution with 39.2% d.m. content. In the process of ultrafiltration (UF), two polymer membranes were used: membrane I with an MWCO (molecular weight cut-off) value of 15–20 kDa and membrane II with MWCO of 6–8 kDa. Nanofiltration (NF) was carried on a polymer membrane with MWCO of 0.5 kDa (membrane III). Effects of UF at 30 and 60 °C, in the range of transmembrane pressure of 1–4 bar, and NF at 30 and 50 °C, in the range of 5–30 bar were examined. In the course of experiments, interdependence between the permeate flux, transmembrane pressure, and volume concentration ratio were followed. The influence of operating parameters (transmembrane pressure, temperature and flow rate) on the efficiency of colored matter removal was examined. Highest separation effects by UF on the examined membranes were achieved for the transmembrane pressure in the range of 2.5–4.0 bar at flow rates ranging from 220 to 360 l/h. Under these conditions, the permeate color was lower by about 55%nd 58% compared with the feed, when using membrane I and membrane II, respectively. Separation of colored matter on membrane III was most efficient when the pressure was held on the level of about 30 bar and at a flow rate ranging from 300 to 400 l/h. Under these conditions, the permeate color decreased by 76%.
Influence of operating parameters on the separation of colorants from sugar house juices by ultra- and nano-filtration
2004, Zuckerindustrie

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Automatic control of the crossflow microfiltration process using fuzzy logic

Abstract

J. Membrane Sci.

J. Food Eng.

Int. J. Man-Machine Studies

Industrial utilization of membranes and membranes processes

Membrane technology in food and bioprocessing

L'utilisation de la microfiltration tangentielle dans le traitement des liquides alimentaires

Process

Aspects Fénéraux de la Commande Floue — Typologie des Contrôleurs Flous