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Mediterranean Conference on control and Automation (MED)

作者： Carlos G. Palacin José Luis Pitarch César de Prada Carlos A. Méndez Systems Engineering and Automatic Control DPT EII Universidad de Valladolid Valladolid Spain Center for Advanced Process Systems Engineering (CAPSE) INTEC (UNL-CONICET) Industrial Engineering DPT (FIQ-UNL) Santa Fe Argentina

ISBN: (纸本)9781509045341

Considering uncertainty in continuous production processes is key to compute short-time optimal schedules which can be trusted in practice. This paper proposes a two-step stochastic approach to the robust scheduling of several evaporation plants. This approach considers the possibility of reacting in the future once the uncertainty materializes. Each evaporator has different features (capacity, equipment, etc.) and the individual performance is affected by external factors and fouling effects. Moreover, a multi-objective analysis has been carried out to provide a decision support for the operator who must take the concrete decisions about load allocation and cleaning tasks along a time horizon. The problem has been solved by discretizing the time horizon and adapting the general-precedence method to deal with an unknown number of tasks. The nonlinear behavior of each plant is approximated by surrogate linear models obtained experimentally, providing thus solutions in acceptable time.

关键词： Cleaning Uncertainty Robustness Job shop scheduling Processor scheduling Computational modeling

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Modifier-Adaptation approach to deal with structural and parametric uncertainty

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IFAC-PapersOnLine 2016年第7期49卷 851-856页

作者： Rodríguez-Blanco, T. Sarabia, D. De Prada, C. Dpt of Systems Engineering and Automatic Control University of Valladolid Doctor Mergelina s/n Valladolid47011 Spain Dpt of Electromechanical Engineering University of Burgos Avda. Cantabria s/n Burgos09006 Spain

Real-Time Optimization (RTO) is not always able to achieve optimal process operation due to the presence of significant uncertainty about the plant models that are used to make decisions and also due to the differences between control architecture layers which operate on different time-scales and use different kind of models. To overcome these issues the economic optimization problem is modified following the Modifier Adaptation methodology to bring the process to the real optimum despite the presence of uncertainty by using plant measurements. To deal with parametric and structural plant-model mismatch, a new approach is presented that combines the estimation of process gradients from transient and steady-state information. It speeds up the convergence of Modifier Adaptation methodology to the process optimum. The approach is illustrated through the simulated example of a depropanizer distillation column. © 2016

关键词： Distillation columns Uncertainty analysis control architecture Economic optimization Estimation of process modifier adaptation Parametric uncertainties Plant model mismatches Real time optimization uncertainty

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Erratum to “Modifier Adaptation methodology based on transient and static measurements for RTO to cope with structural uncertainty” [Comput. Chem. Eng. 106 (2017) 480–500]

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Computers & Chemical engineering 2018年 108卷 460-460页

作者： T. Rodríguez-Blanco D. Sarabia J.L. Pitarch C. de Prada Dpt. of Systems Engineering and Automatic Control University of Valladolid Doctor Mergelina s/n 47011 Valladolid Spain Dpt. of Electromechanical Engineering University of Burgos Avda. Cantabria s/n 09006 Burgos Spain

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Modifier-Adaptation methodology for RTO applied to Distillation Columns using a simplified steady-state model

Modifier-Adaptation methodology for RTO applied to Distillat...

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IEEE Multi-Conference on systems and control

作者： T. Rodriguez-Blanco D. Sarabia C. de Prada Dpt of Systems Engineering and Automatic Control University of Valladolid Dpt of Electromechanical Engineering University of Burgos

ISBN: (纸本)9781509007561

Real-Time Optimization (RTO) is not always able to achieve optimal process operation due to different reasons, among them the presence of significant uncertainty in the plant models that are used to make decisions or the differences between control architecture layers which operate at different time-scales and use different kind of models. To overcome these issues the economic optimization problem, solved in the RTO layer, is modified following the Modifier Adaptation methodology (MA) to bring the process to the real optimum despite the presence of uncertainty by using plant measurements. This paper presents the implementation of MA methodology to the optimal management of distillation columns as a depropanizer column. Specifically, two approaches have been implemented starting from the traditional gradient-based technique called Dual Modifier Adaptation (DMA) to the recent approach Nested Modifier Adaptation (NMA), updating modifiers at the steady state of the process using static information. The RTO layer is based on a really simplified static model of the process which implies the presence of strong structural plant-model mismatch.

关键词： Distillation columns Modifiers static models real time operating system Steady state Mission Assurance

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Hierarchical Optimal Operation of Continuous-Batch Processes

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IFAC-PapersOnLine 2015年第23期48卷 294-301页

作者： De Prada, C. Cristea, S.P. Mazaeda, R. Dpt. of Systems Engineering and Automatic Control University of Valladolid Valladolid47011 Spain

This paper presents a methodology for the optimal operation of mixed continuous-batch processes based on a hierarchical decomposition of the problem: local dynamic optimizers perform the economic optimization of the batch units or continuous plants, while the upper layer deals with the scheduling of the batch units and the coordination of the flows and properties of sub-processes using a novel simplified model built with predictions from the lower level. The approach is illustrated with a case study from the sugar industry corresponding to the joint operation of the evaporation and crystallization sections operated to maximize production with minimum energy consumption. © 2015, IFAC (International Federation of automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Sugar industry Batch data processing Energy utilization Hierarchical systems Optimization Scheduling algorithms Continuous batch Continuous plant Economic optimization Hierarchical control Hierarchical decompositions Minimum energy consumption NMPC Optimal operation

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Autotuning of an in-line pH control system

Autotuning of an in-line pH control system

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Pedro Mercader Kristian Soltesz Alfonso Baños Dpt. Computer and Systems Engineering University of Murcia Murcia Spain Dpt. Automatic Control Lund University Lund Sweden

A novel autotuning procedure is presented through application to an industrial in-line pH control system. The procedure has three advantages over classical relay auto-tuners: experiment duration is very short (no need for limit-cycle convergence); all data is used for identification (instead of only peaks and switch instances); a parameter uncertainty model is identified and utilized for robust controller synthesis.

关键词： Relays Process control Robustness Switches Limit-cycles Convergence

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Plant-wide hierarchical optimal control of a crystallization process

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IFAC-PapersOnLine 2015年第8期48卷 1210-1215页

作者： Rogelio Mazaeda Smaranda P. Cristea Cesar de Prada Dpt.of Systems Engineering and Automatic Control University of Valladolid Spain

This paper deals with the dynamic real time optimization of a benchmark model that represents a genuine problem found at the crystallization section of sugar factories. A most relevant characteristic of the control problem is given by its hybrid nature, mixing continuous control and the scheduling of the crystallizer batch units. The plant-wide optimal control task is approached in a non-centralized hierarchical way with two-layers. The lower layer consists of a set of MPCs, one for each crystallizer, and is in charge of taking the local decisions that minimize an index related with the economic behavior of each unit. The higher level coordinator layer drives the state of the whole plant near the overall economic optimum, while respecting the constraints imposed by the existence of shared resources.

关键词： Predictive control process control hierarchical control integrated scheduling and continuous plant control hybrid optimal control

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Gross error management in data reconciliation

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IFAC-PapersOnLine 2015年第8期48卷 623-628页

作者： M.J. Fuente G. Gutierrez E. Gomez D. Sarabia C. de Prada Dpt. of Systems Engineering and Automatic Control EII University of Valladolid c/ Real de Burgos 47011 Spain Dpt of Electromechanical Eng. University of Burgos Avda. Cantabria s/n 09006 Burgos

This paper reviews the problems associated to the presence of gross errors in data reconciliation problems as well as the main approaches to avoid their undesirable effects: detection and removal of the faulty measurements and minimization of their effect on the reconciled results by using robust estimators that modify the cost function. In the first case, Principal Component Analysis is used to detect the gross errors while, in the second, the Fair function is used. A combined approach is also presented that improves the PCA results. The methods are evaluated in a realistic large-scale problem with plant data corresponding to the hydrogen network of a petrol refinery.

关键词： Data reconciliation Gross error detection PCA robust estimators hydrogen networks

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Modifier-Adaptation methodology for RTO applied to Distillation Columns

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IFAC-PapersOnLine 2015年第8期48卷 223-228页

作者： T. Rodriguez-Blanco D. Sarabia D. Navia C. De Prada Dpt of Systems Engineering and Automatic Control University of Valladolid Doctor Mergelina s/n 47011 Valladolid Spain Dpt of Electromechanical Engineering University of Burgos Avda. Cantabria s/n 09006 Burgos Dpt. Ingenieria Quimica y Ambiental Universidad Tecnica Federico Santa Maria Santiago Chile

Optimal process operation is not always guaranteed due to the presence of significant uncertainty about the plant models that are used to make decisions, for example in Real time optimization, and also due to the differences between control architecture layers which operate on different time-scales and use different kind of models. Modifier adaptation is a methodology that achieves optimality despite the presence of uncertainty by using plant measurements. This paper presents the Nested modifier-adaptation methodology applied to the operation of distillation columns and the results obtained are compared with the previous modifier adaptation methodology using dual control optimization.

关键词： Real Time Optimization modifier-adaptation uncertainty distillation columns optimization problems

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Mixed modifier-adaptation for RTO in a continuous bioreactor 19

Mixed modifier-adaptation for RTO in a continuous bioreactor

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19th IFAC World Congress on International Federation of automatic control, IFAC 2014

作者： Navia, Daniel Gutiérrez, Gloria De Prada, César Dpt. Ingeniería Química y Ambiental Universidad Técnica Federico Santa María Santiago Chile Dpt. Systems Engineering and Automatic Control University of Valladolid c/Real de Burgos s/n Valladolid47011 Spain

ISBN: (纸本)9783902823625

This paper deals with the problem of optimizing the performance of a process using Real Time Optimization (RTO) considering the unavoidable errors in the process models. It implements a new architecture within the modifier-adaptation methodology, presenting a nested optimization problem with two layers. With this methodology, it is possible to find a point that satisfies the KKT conditions of a process using an inaccurate model in the optimization, without the need to estimate directly the experimental gradients of the process. The suggested methodology has been tested in a continuous bioreactor example that present a washout closer to the real optimum of the simulated process. The results show that the proposed methodology is able to find the optimum of the process smoothly, avoiding unstable operating points. © IFAC.

关键词： Bioreactors

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