Authors: None

Abstract:

Keywords:

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.90001

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: ---

Authors: Schuler, Simone; Muenz, Ulrich; Allgower, Frank

Abstract: We consider the problem of constructing decentralized state feedback controllers for linear continuous-time systems. Different from existing approaches, where the topology of the controller is fixed a-priori, the topology of the controller is part of the optimization problem. Structure optimization is done in terms of a minimization of the required feedback and subject to a predefined bound on the tolerable loss of the achieved Hinf-performance of the decentralized controller compared to an Hinf-optimal centralized controller. We develop a computationally efficient formulation of the decentralized control problem by convex relaxations which makes it attractive for practical applications.

Keywords: Model-based Control; Optimization and Scheduling

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00202

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 1-10

Authors: Finkler, Tiago Fiorenzano; Kawohl, Michael; Piechottka, Uwe; Engell, Sebastian

Abstract: In this work, the operation of an industrial semi-batch polymerization reactor is economically optimized using an NMPC scheme. The goal is the minimization of the batch duration without violating the tight constraints for the product specification. Important issues for the practical implementation such as the development and experimental validation of a suitable process model, the estimation of unmeasured states and the real time solution of the nonlinear optimization problem are depicted. The effectiveness of the control scheme is illustrated by results taken from the implementation at the real plant.

Keywords: Model-based Control; Batch Process Modeling and Control; Process and Control Monitoring

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00025

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 11-18

Authors: Trollberg, Olle; Jacobsen, Elling

Abstract: The paper considers extremum seeking control (ESC) for on-line optimization of the CANON process, a new and potentially highly effective process for ammonium removal from wastewater. For gradient estimation we employ the classical method based on periodic excitation. From simulations we find that the ESC scheme can lock onto sub-optimal stationary solutions, far removed from the optimal solution, and that the ESC may have multiple stationary solutions for given controller parameters. The cause of this is investigated through analysis of a general dynamic model. Based on the analysis, it is shown that for systems for which the optimum corresponds to the input-output transfer-function having a transmission zero at the origin, there will in general exist a number of stationary solutions to the ESC with periodic excitation. The solutions are characterized by the phase lag of the system, rather than a zero gradient of the objective function, and are hence in general not related to the optimality conditions. For systems that can be described by Hammerstein or Wiener models, as typically considered in ESC, the solution will in general correspond to the zero gradient condition fulfilled at the optimum. As shown, the CANON process can not be described by Hammerstein or Wiener models, and this then explains the observed existence of sub-optimal stationary solutions.

Keywords: Optimization and Scheduling; Process Applications

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00128

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 19-26

Authors: Gao, Xukai; Chen, Gui; Xie, Lei; Su, Hongye; Wang, Shuqing

Abstract: This article describes mutual information (MI) as a general correlation measure to detect model-plant mismatch (MPM) in nonlinear systems. MI between dithering signals and model residuals is estimated to reveal process MPM regardless of change in disturbance dynamics. Locate the sub-sets of mismatch so that only sub-systems would be perturbed for model updating. The validity of the proposed method for nonlinear systems is illustrated through a numerical example and an industrial PP process.

Keywords: Process and Control Monitoring; Modeling and Identification; Model-based Control

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00002

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 27-32

Authors: Zhang, Bing; Abbas, Ali; Romagnoli, Jose

Abstract: Online monitoring and feedback control are crucial elements in a commercial crystallization operation because they ensure key production variables are closely regulated so as to achieve specified textural and physical properties of the end-product. Digital image texture analysis is a promising method in monitoring and control systems, and is becoming increasingly more attractive due to availability of high speed imaging devices and equally powerful computers. This paper investigates the use of texture analyses in the form of fractal dimension (FD) and energy signatures as characteristic parameters to track the crystal growth. The methodology uses a combination of thresholding and wavelet-texture algorithms. The thresholding method is used to identify crystal clusters and remove empty backgrounds. Wavelet-fractal and energy signatures are performed afterwards to estimate texture on crystal clusters. A series of images obtained at different crystal growth stages during a NaCl-water-ethanol anti-solvent crystallization operation are investigated and their texture characteristics as well as transform tendency during the crystallization process are evaluated.

Keywords: Process and Control Monitoring; Process Applications; Modeling and Identification

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00027

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 33-38

Authors: Galicia, Hector; He, Qinghua (Peter); Wang, Jin

Abstract: Statistics pattern analysis (SPA) is a new multivariate statistical monitoring framework proposed by the authors recently. It addresses some challenges that cannot be readily addressed by the commonly used multivariate statistical methods such as principal component analysis (PCA) in monitoring batch processes in the semiconductor industry. It was later extended to the monitoring of continuous processes using a moving window based approach. In this work, we perform a comprehensive comparison of SPA with representative linear and nonlinear multivariate process monitoring methods. The superior performance of SPA is demonstrated using the challenging Tennessee Eastman process (TEP).

Keywords: Process and Control Monitoring; Process Applications

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00033

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 39-44

Authors: Cecílio, Inês M.; Rapp, Knut; Thornhill, Nina

Abstract: Process auditing using historical data can identify causes for poor performance and reveal opportunities to improve process operation. To date, the data used has been limited to process measurements; however other sources hold complementary information about the process behavior. This paper proposes a new approach to root-cause diagnosis, which also takes advantage of the information in utility, mechanical and electrical data, alarms and diagrams. Its benefit is demonstrated in an industrial case study, by tackling an important challenge in root-cause analysis: large-scale systems. This paper also defines specifications for a semi-automated tool to implement the proposed approach.

Keywords: Process and Control Monitoring

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00059

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 45-50

Authors: Muteki, Koji; Swaminathan, Vidya; Sekulic, Sonja.S; Reid, George. L

Abstract: In pharmaceutical tablet manufacturing processes, a major source of disturbance affecting drug product quality is the (lot to lot) variability of the incoming raw materials. A Feed-Forward process control strategy that compensates for raw material variability is presented. The approach involves building PLS (partial least squares) models that combine raw material attributes and tablet process parameters and relate these to final tablet attributes. The resulting models are used in an optimization framework to then find optimal process parameters which can satisfy all the desired requirements for the final tablet attributes, subject to the incoming raw material lots, prior to performing a batch. The connectivity obtained between the three sources of variability (materials, parameters, attributes) can be considered a design space consistent with Quality by Design (QbD) principles, which is defined by the ICH-Q8 guidance [1]. To implement the FF control, an in-house process simulator is presented. The effectiveness of the methodologies is illustrated through a common industrial tablet manufacturing case study.

Keywords: Process and Control Monitoring; Optimization and Scheduling; Process Applications

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00076

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 51-56

Authors: Yu, Jie

Abstract: Soft sensor technique has become increasingly important to provide reliable on-line measurements, facilitate advanced process control and improve product quality in process industries. The conventional soft sensors are normally single-model based and thus may not be appropriate for processes with shifting operating conditions or phases. In this study, a multiway Gaussian mixture model (MGMM) based kernel partial least squares (PLS) method is proposed to handle multiple operating phases in batch or semibatch processes. The measurement data are first projected onto high-dimensional kernel feature space to account for the process nonlinearity. Then the multiway Gaussian mixture model is estimated with multiple Gaussian clusters in the kernel space. Thus various localized PLS models can be built within each Gaussian cluster to characterize the dynamics in the particular operating phase. Using Bayesian inference strategy, the soft sensor models for all the test samples are adaptively selected from the multiple localized kernel PLS models representing different phases and further used for online quality predictions. The presented soft sensor method is applied to the multiphase penicillin fermentation process and the computational results demonstrate that its performance is superior to the conventional multiway kernel PLS model.

Keywords: Process and Control Monitoring; Batch Process Modeling and Control; Modeling and Identification

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00086

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 57-62

Authors: Hariprasad, K; Bhartiya, Sharad; Gudi, Ravindra

Abstract: Many applications in chemical engineering exhibit a switching character due to discrete and continuous aspects in their dynamic behavior. While first principles models of such systems can be constructed with process simulators, they are usually too complex for use in on line applications such as in model based control. The available methods for modeling of such systems mostly use linear models, such as Mixed Logic Dynamical Systems (MLD) and Piece Wise Affine (PWA) models which describe the evolution of states in each discrete mode using linear equations. Here, we present a modeling strategy for nonlinear switched systems, which is well suited for on-line applications. The method involves a trajectory based linearization and employs a model bank with a set of local linear models for each discrete operational mode. The model bank is generated by linearizing the first principles model across a carefully designed trajectory based on its capability of multi-step ahead prediction. The numerous models are clustered and representative models are selected based on the gap metric as the distance measure. The selected linear models are aggregated using Bayesian or Fuzzy approaches to obtain the global model for the nonlinear switched system. A simulation case study of spherical two tank system is presented to validate proposed modeling strategy.

Keywords: Modeling and Identification; Model-based Control; Process and Control Monitoring

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00030

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 63-68

Authors: Lucia, Sergio; Finkler, Tiago Fiorenzano; Basak, Dahn; Engell, Sebastian

Abstract: In this paper, a non-conservative robust nonlinear model predictive control scheme that can guarantee satisfaction of the constraints and optimal expected performance under uncertainty is introduced. The proposed control scheme is evaluated by simulations using a well known benchmark problem where the operation of a semi-batch polymerization reactors is optimized under very tight temperature tolerance limits. The simulation results show that the proposed scheme is capable of optimizing the process operation and, at the same time, it ensures robust operation within the whole range of uncertainties.

Keywords: Model-based Control; Batch Process Modeling and Control; Optimization and Scheduling

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00035

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 69-74

Authors: Alizadeh Moghadam, Amir; Aksikas, Ilyasse; Dubljevic, Stevan; Forbes, J. Fraser

Abstract: In this contribution a linear quadratic (LQ) control design for a partial differential and algebraic equation (PDAE) system which represents a catalytic distillation process, is presented. The model involves a set of coupled partial differential equations (PDEs), ordinary differential equations (ODEs), and algebraic equations (AEs). The design is based on an infinite-dimensional state-space representation of the system in a Hilbert space and the well-known operator Riccati equation (ORE) method. The underlying PDE-ODE-AE system is converted to one containing coupled PDEs-ODEs, in which the PDE part involves a hyperbolic operator with a space-varying and non-symmetric velocity matrix whose eigenvalues are not necessarily negative through of the domain. Moreover, in the resulting PDE-ODE system, the control variable acts through the ODE part on the boundaries of the PDE section. Using the boundary control transformation method, the PDE-ODE system is represented in an infinite-dimensional state-space with a homogeneous boundary condition. The stabilizability and the detectability properties of the resulting system are explored, which provide guarantees of the existence and uniqueness of the solution to the resulting ORE. The ORE is solved by converting it to a set of equivalent matrix Riccati equations. The designed LQ controller is implemented on the process and its performance is evaluated.

Keywords: Model-based Control; Process Applications

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00111

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 75-80

Authors: Singhal, Martand; Gudi, Ravindra

Abstract: Optimal operation of batch processes in the presence of uncertainty has been an area of significant research interest. The use of online measurements as a source of information offers scope to mitigate the effects of uncertainty and attain optimal operation. Therefore, amongst the different approaches proposed to address the uncertainty issues, measurement based optimization approaches have been shown to be eminently suited. Measurements have been broadly used in two approaches, viz. self optimizing control (SOC) and tracking of necessary conditions of optimality (NCO). In an earlier work for continuous processes by Jaschke and Skogestad [1], the relative complementary roles of NCO tracking and SOC were clearly highlighted in terms of their applicability in combating the effects of different scales of uncertainty and disturbances. For batch processes, the NCO tracking is found to be successful, the complementary role of SOC is largely un-explored. In this work, we extend the integrated approach of Jaschke and Skogestad [1] to batch processes by redefining the NCO and SOC layers. The proposed framework is evaluated using simulations involving a nonlinear batch polymerization of styrene.

Keywords: Optimization and Scheduling; Process Applications; Batch Process Modeling and Control

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00168

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 81-86

Authors: Guay, Martin

Abstract: In this paper, we propose an adaptive optimization technique to solve large scale optimization problems for nonlinear systems composed of multiple interacting agents. The framework is based on the concept of cooperative optimization where each agent addresses a specific local optimization problem that requires information from some or all other agents. An inexact penalty function method is used to solve the overall cooperative optimization problem. The closed-loop follows an adaptive gradient flow that leads to the tracking of local critical points with guaranteed transient performance.

Keywords: Model-based Control; Optimization and Scheduling; Process and Control Monitoring

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00171

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 87-92

Authors: Jahanshahi, Esmaeil; Sigurd, Skogestad; Hansen, Henrik

Abstract: Active control of the production choke valve is the recommended solution to prevent casing-heading instability in gas-lifted oil wells. Focus of this work is to find a simple yet robust control structure for stabilization of the system. In order to find suitable control variables, a controllability analysis of the system with different candidate control variables and two alternative manipulated variables was performed. Moreover, to include robustness and performance requirements at the same time, the controllability analysis was extended to a mixed sensitivity H_inf optimization problem. A control structure using only the available topside pressure measurements was found to be effective to stabilize this system.

Keywords: Process Applications; Model-based Control; Modeling and Identification

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00110

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 93-100

Authors: da Costa Mendes, Paulo Renato; Normey-Rico, Julio Elias; Plucenio, Agustinho; Leão Carvalho, Rodrigo

Abstract: This paper presents a nonlinear predictive controller with a feed-forward action applied to a three-phase separator used in the petroleum industry. Two tools are used in order to include the feed-forward action in the NMPC, a disturbance estimator and a disturbance predictor. Moreover, a supervisory control changes the objetive function characteristics of the NMPC depending on the type of disturbances acting on the process. The separator advanced controller, which is capable to maintain all process variables in pre-defined zones, uses a practical nonlinear model predictive controller (PNMPC) developed in the Department of Automation and Systems (Federal University of Santa Catarina). The performance of the proposed strategy is compared to a traditional PI Zone controller used in industry and to a different NMPC based on a Hammerstein model. All the case study simulations are developed with a complete phenomenological nonlinear model of the separator. The obtained comparative results show that the proposed strategy gives the best results, allowing good oscillation attenuation under slug perturbations.

Keywords: Model-based Control; Modeling and Identification; Process Applications

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00060

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 101-106

Authors: Knudsen, Brage Rugstad; Foss, Bjarne; Whitson, Curtis H.; Conn, Andrew R.

Abstract: The recent success of shale-gas production relies on drilling of long horizontal wells and stimulation with multistage hydraulic fracturing. This practice normally leads to an initial peak production with a subsequent rate decline, followed by low and erratic production rates caused by water accumulation in the wells. Shale-gas recovery requires a large number of wells in order to maintain a sustainable total gas supply. To reduce the surface area disturbances caused by this extensive drilling and to share available surface infrastructure, the use of multi-well pads is a key driver in shale-gas developments. Furthermore, the inherent rate decline of shale-gas wells, the water accumulation in them and the large number of wells, leads to severe operational challenges for well operators. The fact that shut-ins may be used as a means to prevent liquid loading and boost late-life production rates from shale-gas wells, suggests scheduling of shut-ins to perform maintenance and clean-up of the wells, and to track a target rate for the multi-well pad. In this paper we propose an optimization scheme for shale-gas multi-well pads to schedule shut-ins and to track a target rate. The optimization problem is formulated as a discrete time mixed integer linear program (MILP) with binary variables defining at which times the well is either shut-in or producing. A reservoir proxy model and a well model for each well is designed and tuned against a realistic multi-fractured reservoir model. We demonstrate the benefits and the potential of the proposed methodology through a one-month production planning problem for an eight-well shale-gas pad.

Keywords: Optimization and Scheduling; Model-based Control

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00063

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 107-113

Authors: de Prada, Cesar; Gomez Sayalero, Elena; Gutierrez, Gloria; Sarabia, Daniel; Méndez, Carlos A.; Sola, Mikel; González, Rafael

Abstract: This paper describes an approach to optimal management of hydrogen networks in oil refineries,focusing on the problems of reconfiguration that appear when, due to plant failures, the production of the hydrogen generating units suddenly decreases. The problem is formulated in terms of optimization as a MINLP one. Also, guidelines to the implementation of the optimum are presented with the aim of providing a practical solution to the inherent uncertainly and changing dynamics associated to the process.

Keywords: Optimization and Scheduling; Process Applications; Model-based Control

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00144

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 114-119

Authors: Grondin, Félix; Perrier, Michel; Tartakovsky, Boris

Abstract: Laboratory-scale microbial fuel cells are often operated with a constant electrical load. Meanwhile, variations in influent strength and quality, as well as the processes of biofilm growth and decay lead to significant changes of the MFC internal resistance over time. This inevitably results in a mismatch between the internal and the external resistances therefore decreasing MFC power output. This study presents the concept of MFC operation with intermittent connection of the electrical load (external resistance). The efficiency of the proposed method is demonstrated by MFC operation with external resistances significantly below the MFC internal resistance and comparing power outputs obtained using either constant or intermittently connected resistances.

Keywords: Process Applications

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00163

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 120-124

Authors: Eom, Moon-Ho; Kim, Woohyun; Lee, Julia; Lee, Jay H.; Park, Sunwon

Abstract: Adsorption of 1-butanol using adsorbent resin is considered as an energy-efficient method to recover 1-butanol from an acetone-butanol-ethanol (ABE) fermentation broth. To develop the adsorption process, kinetic studies were carried out on adsorption of fermentation products using poly-(styrene-co-divinylbenzene) adsorbent resin. The kinetics for the adsorption of each component were represented in the form of the Langmuir equation and the kinetic parameters were then estimated based on the experimental data. For the parameter estimation of the adsorption model, experiments have been carried out with a batch type slurry adsorption equipment and fermentation model broth, containing acetone, ethanol, 1-butanol, acetic acid, and butyric acid. It was found that the extended Langmuir model derived from single component adsorption can correctly predict the competitive adsorption of multi-component mixture. The developed kinetic models are validated by the experiment using the actual broth. This study is expected to contribute to designing a large-scale biobutanol recovery process.

Keywords: Process Applications; Modeling and Identification

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00176

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 125-130

Authors: Behrendt, Martin; Bajcinca, Naim; Zenith, Federico; Krewer, Ulrike

Abstract: This paper considers optimal operation of an hybrid powered energy system. The two power sources include a direct methanol fuel cell and a lithium-ion battery. A portable system represented by characteristic dynamic load profiles is considered as the consumer. A PI and a nonlinear model predictive control algorithm have been investigated and compared in terms of efficiency and robustness of operation.

Keywords: Model-based Control; Process Applications; Optimization and Scheduling

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00184

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 131-136

Authors: Suvarov, Paul; Vande Wouwer, Alain; Kienle, Achim

Abstract: Simulated moving bed (SMB) is a continuous chromatographic process used for the separation of chemical mixtures. This paper presents an almost plug-and-play control strategy, which requires little prior knowledge about the adsorption properties. A discrete-time nonlinear model derived from the wave theory is the basis to control the position of the adsorption and desorption fronts. The front velocities are estimated on-line enabling the compensation of initial parameter discrepancies, and drift due to column aging or temperature fluctuation. The overall performance of the control strategy is evaluated using numerical simulation for two case studies relative to the separation of fructo-oligosaccharides and cyclopentanone – cycloheptanone, respectively.

Keywords: Model-based Control; Batch Process Modeling and Control

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00098

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 137-142

Authors: Kozma, Attila; Andersson, Joel; Savorgnan, Carlo; Diehl, Moritz

Abstract: Large interconnected systems consist of a multitude of subsystems with their own dynamics, but coupled with each other via input-output connections. Each subsystem is typically modelled by ordinary differential equations or differential-algebraic equations. Simulation and optimal control of such systems pose a challenge both with respect to CPU time and memory requirements. We address optimal control of such systems by applying ”distributed multiple shooting”, a generalization of the direct multiple shooting method, which uses the decomposable structure of the system in order to obtain a highly parallel algorithm. The interconnections are allowed to be infeasible during the iterations but are driven to feasibility by a Newton-type optimization algorithm. We evaluate the performance of the distributed multiple shooting method on a large scale estimation problem.

Keywords: Optimization and Scheduling; Model-based Control

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00162

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 143-147

Authors: Miao, Aimin; Song, Zhi-Huan; Wen, Qiaojun; Ge, Zhiqiang

Abstract: A new orthogonal neighborhood preserving embedding (ONPE) and its kernel generalization based process monitoring approaches are presented in this paper. ONPE aims at preserving local neighborhood structure of process data while reducing data dimensionality. As an approximation of the nonlinear manifold learning method, ONPE is capable to handle process nonlinearity. Moreover, to enhance the nonlinear modeling performance, the nonlinear extension of ONPE is also developed, with the introduction of kernel-tricks. By constructing monitoring statistics, both ONPE and its generalization are applied for fault detection in nonlinear processes. Two case studies show the superiority of the proposed method in process monitoring.

Keywords: Process and Control Monitoring

Digital Object Identifier (DOI): 10.3182/20120710-4-SG-2026.00097

Conference: 8th IFAC International Symposium on Advanced Control of Chemical Processes (2012)

Location: Furama Riverfront, Singapore

Start Date: Tue Jul 10 2012 - End Date: Fri Jul 13 2012

Page Numbers: 148-153