Comparative performance of concentration and temperature controlled batch crystallizations

Nagy, Zoltán K.; Chew, Jia Wei; Fujiwara, Mitsuko; Braatz, Richard D.

doi:10.1016/j.jprocont.2007.10.006

Cited by 159 publications

(124 citation statements)

References 26 publications

Supporting

Mentioning

120

Contrasting

Unclassified

Order By: Relevance

“…Based on the conventional PID control structure, the proposed indirect-type ILC scheme is shown in Figure 1, as outlined by the dash-line box, where the learning controllers, 1 L , 2 L , 3 L , are set to adjust the setpoint command, i.e.…”

Section: Problem Formulationmentioning

confidence: 99%

“…In fact, all the feedforward controllers, 1 F , 2 F , 3 F , corresponding to 1 F , 2 F , 3 F in (40) that may be viewed as slack variables to facilitate the LMI feasibility, are used to increase the flexibility of the indirect-type ILC in the proposed control scheme shown in Figure 1, for the purpose of robustly tracking the desired output profile against process uncertainties and load disturbance.…”

Section: Robust Indirect-type Ilc Designmentioning

confidence: 99%

“…Similarly, by specifying the learning controllers, 1 L , 2 L , 3 L , which determine the convergence rate of the ILC scheme, the achievable robust performance can be assessed through the LMI condition in (40), and so is for the allowable process uncertainty bounds denoted by ( , 1) A t k  and ( , 1) B t k  . Note that the allowable variation of initial process conditions from batch to batch can also be assessed through the LMI condition in (40) by lumping the variation bound into the magnitude ( w D ) of the disturbance as shown in (9) and (37).…”

Section: Robust Indirect-type Ilc Designmentioning

confidence: 99%

“…With the wide application of ILC in engineering applications in the recent years, it has become increasingly appealing to develop robust ILC methods to deal with time-varying uncertainties occurring in a cycle or cycle-to-cycle (batchwise) uncertainties, because many batch processes, e.g., industrial injection molding and pharmaceutical crystallization, are slowly varying from batch to batch, while repeating fundamental dynamic response characteristics [1][2][3][4]. As surveyed by Bonvin et al [5], Ahn et al [6], and Wang et al [7], most of existing references have been devoted to time-invariant linear or nonlinear batch processes.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Robust PID based indirect-type iterative learning control for batch processes with time-varying uncertainties

Liu

Wang

Chen

2014

Journal of Process Control

View full text Add to dashboard Cite

Based on the proportional-integral-derivative (PID) control structure widely used in engineering applications, a robust indirect-type iterative learning control (ILC) method is proposed for industrial batch processes subject to time-varying uncertainties. An important merit is that the proposed ILC design is independent of the PID tuning that aims primarily to hold robust stability of the closed-loop system, owing to the fact that the ILC updating law is implemented through adjusting the setpoint of the closed-loop PID control structure plus a feedforward control to the plant input from batch to batch. According to the robust H infinity control objective, a robust discrete-time PID tuning algorithm is given in terms of the plant state-space model description to accommodate for time-varying process uncertainties. For the batchwise direction, a robust ILC updating law is developed based on the two-dimensional (2D) control system theory. Only measured output errors of current and previous cycles are used to implement the proposed ILC scheme for the convenience of practical application. An illustrative example from the literature is adopted to demonstrate the effectiveness and merits of the proposed ILC method.

show abstract

Section: Problem Formulationmentioning

confidence: 99%

Section: Robust Indirect-type Ilc Designmentioning

confidence: 99%

Section: Robust Indirect-type Ilc Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust PID based indirect-type iterative learning control for batch processes with time-varying uncertainties

Liu

Wang

Chen

2014

Journal of Process Control

View full text Add to dashboard Cite

show abstract

“…Since the metastable zone width (MSZW) is not a thermodynamic property it changes in function of several system characteristics such as: cooling rate, degree of stirring, solution history and presence of foreign particles (impurities or additives). The accurate determination of the metastable zone allows improved supersaturation control policies, it helps to avoid secondary nucleation, ensures maximal productivity and the desired particle size distribution (PSD) at the end of the batch (Braatz, 2002, Nagy et al, 2008.…”

Section: Introductionmentioning

confidence: 99%

Comparison of external bulk video imaging with focused beam reflectance measurement and ultra-violet visible spectroscopy for metastable zone identification in food and pharmaceutical crystallization processes

Simon

Nagy

Hungerbühler

2009

Chemical Engineering Science

Self Cite

View full text Add to dashboard Cite

• This is a journal article. It was published in the Chemical Engi- The purpose of the paper is twofold: it describes the proof of concept of the newly introduced bulk video imaging (BVI) method and it presents the comparison with existing process analytical technologies (PAT) such as focused beam reflectance measurement (FBRM) and ultra violet/visible (UV/Vis) spectroscopy. While the latter two sample the system in small volumes closely to the probe, the BVI approach monitors the entire or large parts of the crystallizer volume. The BVI method is proposed as a complementary noninvasive PAT tool and it is shown that it is able to detect the boundaries of the metastable zone with comparable or better performance than the FBRM and UV/VIS probes.

show abstract

Continuous Crystallisation

Brown

McGlone

Florence

2017

Continuous Manufacturing of Pharmaceuticals

View full text Add to dashboard Cite

Mixing 2) Nucleation 3) Growth 4) Filter/wash/dry Required to:  Produce consistent composition  Control crystallisation driving force  Influence flow rate, shear-kinetic effects  Consistent suspension of seed and product Controlled via:  Supersaturation  High shear  External fields, e.g. ultrasound, nonphotochemical laser induced nucleation  Seed. Seeds produced via dry milling, wet media milling, precipitation, recycle, dissolution, spray drying or secondary nucleation Controlled to avoid:  Fouling  Agglomeration  Dissolution  Crystalline form transformation(s) Controlled via:  Supersaturation (typically low) via cooling, anti-solvent, evaporation  Effective heat/mass transfer Ensures:  Efficient desupersaturation Controlled to avoid:  Fouling  Agglomeration  Attrition (particle breakage)  Dissolution  Crystalline form transformation(s) Required to:  Create filter cake  Remove mother liquor and impurities  Maintain particle attributes Controlled to avoid:  Agglomeration  Attrition (particle breakage)Continuous crystallisation has been implemented for many decades in other manufacturing sectors, typically for large volume commodity chemicals, and offers a range of potential advantages [16,17] including lower operating and capital costs, reduced down time and more efficient use of energy and materials. Cooling and anti-solvent crystallisation are commonly used in industrial applications and can be readily implemented in continuous. The aim is to follow a controlled trajectory through the solubility phase diagram (section 1.2).

show abstract

Comparative performance of concentration and temperature controlled batch crystallizations

Cited by 159 publications

References 26 publications

Robust PID based indirect-type iterative learning control for batch processes with time-varying uncertainties

Robust PID based indirect-type iterative learning control for batch processes with time-varying uncertainties

Comparison of external bulk video imaging with focused beam reflectance measurement and ultra-violet visible spectroscopy for metastable zone identification in food and pharmaceutical crystallization processes

Continuous Crystallisation

Contact Info

Product

Resources

About