Model-based optimization and control of chromatographic processes

Klatt, Karsten‐Ulrich; Hanisch, Felix; Dünnebier, Guido; Engell, Sebastian

doi:10.1016/s0098-1354(00)00492-0

Cited by 83 publications

(41 citation statements)

References 10 publications

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“…The HPLC separation system operated in batch mode is characterized by subsequent pulse injections of the sample mixture and relies on pumps to pass a pressurized liquid solvent containing the sample mixture through a column packed with a solid adsorbent material [52]. A simplified P&ID of a standard HPLC system under consideration is illustrated in Figure 1.…”

Section: Process Descriptionmentioning

confidence: 99%

Methods and Tools for Robust Optimal Control of Batch Chromatographic Separation Processes

et al. 2015

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This contribution concerns the development of generic methods and tools for robust optimal control of high-pressure liquid chromatographic separation processes. The proposed methodology exploits a deterministic robust formulation, that employs a linearization of the uncertainty set, based on Lyapunov differential equations to generate optimal elution trajectories in the presence of uncertainty. Computational tractability is obtained by casting the robust counterpart problem in the framework of bilevel optimal control where the upper level concerns forward simulation of the Lyapunov differential equation, and the nominal open-loop optimal control problem augmented with the robustified target component purity inequality constraint margin is considered in the lower level. The lower-level open-loop optimal control problem, constrained by spatially discretized partial differential equations, is transcribed into a finite dimensional nonlinear program using direct collocation, which is then solved by a primal-dual interior point method. The advantages of the robustification strategy are highlighted through the solution of a challenging ternary complex mixture separation problem for a hydrophobic interaction chromatography system. The study shows that penalizing the changes in the zero-order hold control gives optimal solutions with low sensitivity to uncertainty. A key result is that the robustified general elution trajectories outperformed the conventional linear trajectories both in terms of recovery yield and robustness.

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Section: Process Descriptionmentioning

confidence: 99%

Methods and Tools for Robust Optimal Control of Batch Chromatographic Separation Processes

et al. 2015

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“…The chromatographic separation can be described by a number of numerical models (see, for instance, [33][34][35]); in this work we consider the following CDR system:…”

Section: Experiments 3: Chromatographic Separationmentioning

confidence: 99%

Particle transport method for convection problems with reaction and diffusion

Shipilova¹,

Haario²,

Smolianski³

2007

Numerical Methods in Fluids

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SUMMARYThe paper is devoted to the further development of the particle transport method for the convection problems with diffusion and reaction. Here, the particle transport method for a convection-reaction problem is combined with an Eulerian finite-element method for diffusion in the framework of the operator-splitting approach. The technique possesses a special spatial adaptivity to resolve solution singularities possible due to convection and reaction terms. A monotone projection technique is used to transfer the solution of the convection-reaction subproblem from a moving set of particles onto a fixed grid to initialize the diffusion subproblem. The proposed approach exhibits good mass conservation and works with structured and unstructured meshes.The performance of the presented algorithm is tested on one-and two-dimensional benchmark problems. The numerical results confirm that the method demonstrates good accuracy for the convection-dominated as well as for convection-diffusion problems.

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“…Several reports on dynamic control strategies include nonlinear control strategies such as: (a) the input-output linearizing control, where the controller action is based on a nonlinear state estimator using the TMB model (Kloppenburg and Gilles, 1999); (b) repetitive model predictive control (RMPC) (Natajan and Lee, 2000; Abel et al, 2004;Erdem et al, 2004b). Also a model based SMB control where an optimal trajectory calculated off-line should be followed was proposed by Klatt et al, 2000. A more recent strategy based on the nonlinear wave propagation phenomena aims to control the central sections of the SMB unit by controlling the position of the concentration fronts (Schramm et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

Simulated moving bed technology: old and new

2006

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The Simulated Moving Bed (SMB) concept has been applied to the separation of different mixtures as a continuous counter current separation process, avoiding several problems related with solid motion. The aim of this work is to present some relevant examples of SMB separations corresponding to the two major ages in the use of the SMB concept, here named "old" and "new" applications. The "old" applications of SMB technology in the petrochemical industry are still important, with large and highly productive units; and the "new" applications of the second "age" of SMB concept are from the fine chemical, pharmaceutical and biochemistry areas, associated with the demand of high purity products during the last 10 years. Different examples are presented for different ages: a UOP Parex R process for the "old", modelled with the equivalent True Moving Bed (TMB) approach; and a chiral resolution for the "new", modelled by the real SMB model. Some of the latest developments are also mentioned: the non conventional techniques as the Varicol R process, PowerFeed, Modicon, M3C or Enriched Extract-SMB (EE-SMB), MultiFeed (MF), Outlet Streams Swing (OSS) or Pseudo-SMB, involving considerable changes in the SMB concept itself. The use of the last optimization/modelling packages P. Sá Gomes . M. Minceva . A. E. Rodrigues ( ) Laboratory of Separation and Reaction Engineering

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Model-based optimization and control of chromatographic processes

Cited by 83 publications

References 10 publications

Methods and Tools for Robust Optimal Control of Batch Chromatographic Separation Processes

Methods and Tools for Robust Optimal Control of Batch Chromatographic Separation Processes

Particle transport method for convection problems with reaction and diffusion

Simulated moving bed technology: old and new

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