An optimal control approach to steam distillation of essential oils from aromatic plants

Valderrama, Freddy; Ruiz, Fredy

doi:10.1016/j.compchemeng.2018.05.009

Cited by 42 publications

(29 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lower indices: f -feed parameter; fl -phlegm parameter; i -number of mixture components. The proposed method of rectification process optimization consists of the following steps: 1) Limit values of technical-economical process variables in (6) and 8are determined by solving optimization problems using each particular criterion alone.…”

Section: Methods For Optimizing the Rectification Process Using Mobilementioning

confidence: 99%

“…Following control systems for rectification columns can be outlined: robust [2], adaptive [3,4], supervised [5], optimal [6,7], control systems involving neural networks [8], fuzzy logic [9], non-linear prediction process model [10,11]. The quality and effectiveness of such systems can be improved with the use of distributed [12] or mobile [13,14] control actions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimization of Rectification Process Using Mobile Control Action With Account for Criterion of Maximizing Separation Quality

Sheikus¹,

Кovalenko²,

Kotok³

et al. 2020

Eureka: PE

View full text Add to dashboard Cite

The use of mobile control action allows the improvement of technical-economical characteristics of the rectification process and allows for operation regimes that can’t be achieved with traditional control approaches. Mobility lies in the ability to choose the movement law of compound source and energy in the spatial region of apparatus. Mobile control over the rectification process can be realized by changing the column feed point. An optimal number of feed trays must be determined with consideration of cost and output performance, and also the quality of the target product. The work aimed to develop a method for calculating optimal control action, including mobile ones, on the rectification process with additional account for the criterion of maximizing quality of target product, and also, comparison of static column profiles that are optimal by different criteria. Mathematical modeling of the rectification column for separation of water-methanol mixture revealed that increasing quality requirements to target products decreases the number of the optimal feed tray. A method was described for process optimization by the normalized criterion that accounts for separation quality and power consumption. The method was used to determine optimal values of traditional (flows of heat into the column's cube and phlegm) and mobile (feed tray number) control actions that provide the best technical-economical parameters of the rectification column. A proof is presented for the existence and uniqueness of solutions for this optimization problem and the effectiveness of using mobile actions for different requirements to target. The optimal temperature profile of the culms was studied and their characteristic features that correspond to different specific and normalized optimization criteria were found

show abstract

Section: Methods For Optimizing the Rectification Process Using Mobilementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Rectification Process Using Mobile Control Action With Account for Criterion of Maximizing Separation Quality

Sheikus¹,

Кovalenko²,

Kotok³

et al. 2020

Eureka: PE

View full text Add to dashboard Cite

show abstract

“…Additional example problems are shown in the back matter, with an example of an artificial neural network in Appendix A and several dynamic optimization benchmark problems shown in Appendix B. Since the GEKKO Fortran backend is the successor to APMonitor [37], the many applications of APMonitor are also possible within this framework, including recent applications in combined scheduling and control [46], industrial dynamic estimation [43], drilling automation [47,48], combined design and control [49], hybrid energy storage [50], batch distillation [51], systems biology [44], carbon capture [52], flexible printed circuit boards [53], and steam distillation of essential oils [54].…”

Section: Examplesmentioning

confidence: 99%

GEKKO Optimization Suite

et al. 2018

View full text Add to dashboard Cite

This paper introduces GEKKO as an optimization suite for Python. GEKKO specializes in dynamic optimization problems for mixed-integer, nonlinear, and differential algebraic equations (DAE) problems. By blending the approaches of typical algebraic modeling languages (AML) and optimal control packages, GEKKO greatly facilitates the development and application of tools such as nonlinear model predicative control (NMPC), real-time optimization (RTO), moving horizon estimation (MHE), and dynamic simulation. GEKKO is an object-oriented Python library that offers model construction, analysis tools, and visualization of simulation and optimization. In a single package, GEKKO provides model reduction, an object-oriented library for data reconciliation/model predictive control, and integrated problem construction/solution/visualization. This paper introduces the GEKKO Optimization Suite, presents GEKKO’s approach and unique place among AMLs and optimal control packages, and cites several examples of problems that are enabled by the GEKKO library.

show abstract

“…A recent comparison of the two methods showed that vapour infusion resulted in higher extraction of monoterpenes than steep infusion . The mix of ethanol‐water vapour passes through the plant material and extracts the desired flavour compounds , characterised by: Entrance of the solvent into the plant matrix Solubilisation of compound/thermal oil exudation from the plant Transport of compounds to the outside Vapour‐liquid equilibrium at the surface layer Vapourisation …”

Section: Introductionmentioning

confidence: 99%

Influence of distillation parameters on the extraction of Juniperus communis L . in vapour infused gin

2020

View full text Add to dashboard Cite

The influence of distillation parameters on the extraction of flavour compounds from the gin botanical Juniperus communis L. using vapour infusion was investigated. The optimum mix of conditions to extract the highest levels of certain compounds was established using a 3 3 -factorial design. Quantification using solid-phase microextraction and gas chromatography coupled mass spectrometry, was performed measuring nine common flavour compounds. The greatest influence was the botanical ratio, whilst the least influential parameter was ethanol concentration for all compounds except terpinen-4-ol. Density functional theory calculations of quantitative structure-activity relationship properties for the flavour compounds were also undertaken to test for molecular influence on solvent extraction. The quantitative structure-activity relationship model showed the highest dipole moment for terpinen-4-ol and the lowest for γ-terpinene.

show abstract

An optimal control approach to steam distillation of essential oils from aromatic plants

Cited by 42 publications

References 26 publications

Optimization of Rectification Process Using Mobile Control Action With Account for Criterion of Maximizing Separation Quality

Optimization of Rectification Process Using Mobile Control Action With Account for Criterion of Maximizing Separation Quality

GEKKO Optimization Suite

Influence of distillation parameters on the extraction of Juniperus communis L . in vapour infused gin

Contact Info

Product

Resources

About