Combined Estimation and Optimal Control of Batch Membrane Processes

Jelemenský, Martin; Pakšiová, Daniela; Paulen, Radoslav; Latifi, Abderrazak M.; Fikar, Miroslav

doi:10.3390/pr4040043

Cited by 4 publications

(4 citation statements)

References 31 publications

(36 reference statements)

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“…Measurement of the fluid flow at the desired pressure drop. The measurement of the fluid flow was repeated to control possible changes in the filter characteristics due to fouling [32]. The fouling might have been caused by some algae [33] or micro-corrosion in the water tank.…”

Section: Testing Proceduresmentioning

confidence: 99%

Development of an Experimental Dead-End Microfiltration Layout and Process Repeatability Analysis

Bombek,

Kevorkijan,

Hrovat

et al. 2024

Processes

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Microfiltration is an important process in the pharmaceutical industry. Filter selection and validation is a time-consuming and expensive process. Quality by design approach is important for product safety. The article covers the instrumentalization and process control of a laboratory-scale dead-end microfiltration layout. The layout is a downscale model of the actual production line, and the goal is filter validation and analysis of process parameters, which may influence filter operation. Filter size, fluid pressure, valve plunger speed, and timing issues were considered. The focus is on the identification of the most influential process parameters and their influence on the repeatability of pressure oscillations caused by valve opening. The goal was to find the worst-case scenario regarding pressure oscillations and, consequently, filter energy intake. The layout was designed as compact as possible to reduce pressure losses between the filter and valve. Valve-induced pressure oscillations proved to be prevailing over the water hammer effect. Several filters in sizes between 3.5 cm2 and 6900 cm2 were tested, and some recommendations were suggested for the reduction of energy intake of the filter and to improve the repeatability of the process.

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Section: Testing Proceduresmentioning

confidence: 99%

Development of an Experimental Dead-End Microfiltration Layout and Process Repeatability Analysis

Bombek,

Kevorkijan,

Hrovat

et al. 2024

Processes

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“…13,17,21 However, the standard LS approach assumes that different output data have same contributions to the estimation of unknown parameters. 22 Therefore, the weighted least-squares (WLS) method was developed, whereby suitable weights are assigned to the relevant residuals. 19,23 The relatively compact form and high computational efficiency of the WLS approach have led to its widespread application to parameter estimation problems in various chemical processes.…”

Section: Introductionmentioning

confidence: 99%

“…In recent decades, a great number of methods have been developed for implicit parameter estimation. Among these, the most popular one is the least-squares (LS) approach, in which the objective function is generally defined as a summation of the 2-norm residuals of output variables between model prediction and measurement. ,, However, the standard LS approach assumes that different output data have same contributions to the estimation of unknown parameters . Therefore, the weighted least-squares (WLS) method was developed, whereby suitable weights are assigned to the relevant residuals. , The relatively compact form and high computational efficiency of the WLS approach have led to its widespread application to parameter estimation problems in various chemical processes. − The WLS approach assumes that the input variables can be precisely measured and that there are no errors in the input data.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling for the Industrial 2-Mercaptobenzothiazole Batch Production Process

Liang

Song²,

Liu³

et al. 2022

ACS Omega

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As an important chemical intermediate, 2-mercaptobenzothiazole (MBT) is widely used in various processes, especially in the rubber industry. However, there is no first-principles model that describes the synthetic process of MBT. This paper focuses on the formulation of a reliable mathematical model represented by a series of differential and algebraic equations for the industrial batch MBT production process. It is difficult to estimate all of the unknown parameters in the model because of the lack of sufficient industrial/experimental data. Thus, a reduced estimable parameter set is derived by performing estimability analysis on the original estimation problem. A multiple-starting-point strategy is then applied to numerically solve the non-convex parameter estimation problem with the weighted least-squares approach. Subsequently, a cross-validation technique is employed to evaluate the generalizability of the proposed model. Finally, it is confirmed that the proposed model produces encouraging prediction performance with regard to independent test data.

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“…This special issue on real-time optimization (http://www.mdpi.com/journal/processes/special_ issues/real_time_optimization) includes both methodological and practical contributions [1][2][3][4][5][6][7][8][9][10][11][12][13]. All seven methodological contributions deal with explicit RTO schemes that repeat the optimization when new measurements become available.…”

mentioning

confidence: 99%

Special Issue “Real-Time Optimization” of Processes

Bonvin

2017

Processes

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Process optimization is the method of choice for improving the performance of industrial processes, while also enforcing the satisfaction of safety and quality constraints. Long considered an appealing tool but only applicable to academic problems, optimization has now become a viable technology. Still, one of the strengths of optimization-namely, its inherent mathematical rigor-can also be perceived as a weakness, since engineers might sometimes find it difficult to obtain an appropriate mathematical formulation to solve their practical problems. Furthermore, even when process models are available, the presence of plant-model mismatches and process disturbances makes the direct use of model-based optimal inputs hazardous. In the last 30 years, the field of real-time optimization (RTO) has emerged to help overcome the aforementioned modeling difficulties. RTO integrates process measurements into the optimization framework. This way, process optimization does not rely exclusively on a (possibly inaccurate) process model but also on process information stemming from measurements. Various RTO techniques are available in the literature and can be classified in two broad families depending on whether a process model is used (explicit optimization) or not (implicit optimization).This special issue on real-time optimization (http://www.mdpi.com/journal/processes/special_ issues/real_time_optimization) includes both methodological and practical contributions [1][2][3][4][5][6][7][8][9][10][11][12][13]. All seven methodological contributions deal with explicit RTO schemes that repeat the optimization when new measurements become available. The methods covered include modifier adaptation, economic MPC, and the two-step approach of parameter identification and numerical optimization. The six contributions that deal with applications cover various fields including refineries, well networks, combustion, and membrane filtration.This special issue shows that RTO is a very active area of research with excellent opportunities for applications. The guest editor would like to thank all authors for their timely collaboration on this project and excellent scientific contributions. References

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Combined Estimation and Optimal Control of Batch Membrane Processes

Cited by 4 publications

References 31 publications

Development of an Experimental Dead-End Microfiltration Layout and Process Repeatability Analysis

Development of an Experimental Dead-End Microfiltration Layout and Process Repeatability Analysis

Mathematical Modeling for the Industrial 2-Mercaptobenzothiazole Batch Production Process

Special Issue “Real-Time Optimization” of Processes

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