Combined model approximation techniques and multiparametric programming for explicit nonlinear model predictive control

Rivotti, Pedro; Lambert, Romain; Pistikopoulos, Efstratios N.

doi:10.1016/j.compchemeng.2012.01.009

Cited by 39 publications

(14 citation statements)

References 22 publications

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“…Usually, the models designed in the previous step contain large sets of Partial and/or Ordinary Differential and Algebraic Equations (PDAE and/or ODAE) that involve highly nonlinear terms, thus leading to computationally expensive simulations. Therefore, it is often necessary to simplify the model formulation and replace it with a linear system representation that will allow control studies to be successfully performed . PAROC suggests the model approximation to be realized via either (i) system identification or (ii) model reduction techniques.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Advanced model‐based control strategies for the intensification of upstream and downstream processing in mAb production

Papathanasiou

Quiroga-Campano

Steinebach

et al. 2017

Biotechnology Progress

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Current industrial trends encourage the development of sustainable, environmentally friendly processes with minimal energy and material consumption. In particular, the increasing market demand in biopharmaceutical industry and the tight regulations in product quality necessitate efficient operating procedures that guarantee products of high purity. In this direction, process intensification via continuous operation paves the way for the development of novel, eco-friendly processes, characterized by higher productivity and lower production costs. This work focuses on the development of advanced control strategies for (i) a cell culture system in a bioreactor and (ii) a semicontinuous purification process. More specifically, we consider a fed-batch culture of GS-NS0 cells and the semicontinuous Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) for the purification process. The controllers are designed following the PAROC framework/software platform and their capabilities are assessed in silico, against the process models. It is demonstrated that the proposed controllers efficiently manage to increase the system productivity, returning strategies that can lead to continuous, stable process operation. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:966-988, 2017.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Advanced model‐based control strategies for the intensification of upstream and downstream processing in mAb production

Papathanasiou

Quiroga-Campano

Steinebach

et al. 2017

Biotechnology Progress

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“…The sensitivity analysis indices are usually computed through Monte-Carlo numerical integration Kontoravdi et al (2005), Kontoravdi et al (2010), Yue et al (2008), and Kiparissides et al (2009) Use of sensitivity analysis in the context of biomedical engineering in order to asses the robustness of complex biological and biomedical models and quantify uncertainty Homma and Saltelli (1996), Saltelli et al (2000), and Saltelli et al (2010) Development of global sensitivity analysis as a tool to detect parameter interactions, in particular variance based methods Narciso and Pistikopoulos (2008) Combination of linear model reduction and linear multi-parametric model-predictive control (mp-MPC) Rivotti et al (2012) A model order reduction via empirical Grammians (Hahn and Edgar, 2002) is combined with a mp-MPC algorithm Lambert et al (2013a) Using Monte-Carlo integrations, N step ahead affine representations are created policies. The calculation of such policies, e.g.…”

Section: Referencementioning

confidence: 99%

“…The examined process model is characterised by highly nonlinear sets of PDAEs that need to be simplified in order to be used for control studies (Lambert et al, 2013a;Rivotti et al, 2012). Therefore, we apply a system identification step, where we design three discrete, linear, state space models that captures the system dynamics.…”

Section: System Identificationmentioning

confidence: 99%

PAROC—An integrated framework and software platform for the optimisation and advanced model-based control of process systems

Pistikopoulos

Diangelakis

Oberdieck

et al. 2015

Chemical Engineering Science

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131

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“…The state space model constitutes an intermediate step used only for the formulation and the solution of the multiparametric programming problem. 33,42 For the identification procedure, we excite the high fidelity model under random pulse input disturbance within the range of interest ( Figure 5). More specifically, we vary both the input (modifier concentration) and the disturbances (feed composition), as in this case the latter can be predicted by experimental procedures and is, therefore, treated as measured disturbance.…”

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confidence: 99%

Advanced control strategies for the multicolumn countercurrent solvent gradient purification process

et al. 2016

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The multicolumn countercurrent solvent gradient purification process (MCSGP) is a semicontinuous, chromatographic separation process used in the production of monoclonal antibodies) . The process is characterized by high model complexity and periodicity that challenge the development of control strategies, necessary for feasible and efficient operation and essential toward continuous production. A novel approach for the development of control policies for the MCSGP process, which enables efficient continuous process control is presented. Based on a high fidelity model, the recently presented PAROC framework and software platform that allows seamless design and in-silico validation of advanced controllers for complex systems are followed. The controller presented in this work is successfully tested against disturbances and is shown to efficiently capture the process periodic nature. V C 2016 American Institute of Chemical Engineers AIChE J, 62: 2341AIChE J, 62: -2357AIChE J, 62: , 2016 Keywords: process control, continuous biomanufacturing, multiparametric control IntroductionMonoclonal antibodies (mAbs) play a vital role in the treatment of infectious diseases, cancer, and autoimmune diseases.1 They are characterized, however, by high prices (approximately $35000 p/a per patient for mAbs treating cancer conditions) 2 that arise from their high production costs. Although over the past few years their market has been rapidly increasing, 3 the emergence of biosimilars and the introduction of novel therapeutic agents drives their biomanufacturing toward alternative routes of lower operating costs. 4 MAb production consists of the upstream processing (USP), where the cells are cultured and the therapeutic agent is produced, and the downstream processing (DSP) that involves the isolation/ purification steps of the targeted product. Under high titers, however, DSP can become significantly expensive, mostly due to equipment and consumables costs. [5][6][7][8][9] This along with the increasing demand on product quality and higher titers 3,5 drive advances in mAb biomanufacturing toward continuous operation. 4 Here, we focus on the development of advanced control strategies for the multicolumn countercurrent solvent gradient purification process (MCSGP), 10 aiming to drive the system toward continuous operation. MCSGP is a semicontinuous, chromatographic separation process of biomolecules, based on ion-exchange firstly presented by . 11 The process is described by complex partial differential and algebraic equations (PDAEs), involving highly nonlinear terms and is governed by periodic operation profiles that render control studies difficult to perform. There have been several works that have studied the optimization and control of such systems. Degerman et al. (2006) 12 use a nonlinear performed optimization studies on a nonlinear chromatography model to define the optimal operation points that will meet the purity Corresponding concerning this article should be addressed to E. Pistikopoulos at stratos@tamu.edu. constrai...

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Combined model approximation techniques and multiparametric programming for explicit nonlinear model predictive control

Cited by 39 publications

References 22 publications

Advanced model‐based control strategies for the intensification of upstream and downstream processing in mAb production

Advanced model‐based control strategies for the intensification of upstream and downstream processing in mAb production

PAROC—An integrated framework and software platform for the optimisation and advanced model-based control of process systems

Advanced control strategies for the multicolumn countercurrent solvent gradient purification process

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