Alejandro Gabriel Marchetti

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Related publications (31)

Real-time Optimization with Estimation of Experimental Gradient

Dominique Bonvin, Alejandro Gabriel Marchetti, Benoît Chachuat

For good performance in practice, real-time optimization schemes need to be able to deal with the inevitable model-mismatch problem. Unlike the two-step schemes combining parameter estimation and optimization, the modifier-adaptation approach uses experime ...

2009

Modifier-adaptation methodology for real-time optimization

Alejandro Gabriel Marchetti

The process industries are characterized by a large number of continuously operating plants, for which optimal operation is of economic importance. However, optimal operation is particularly difficult to achieve when the process model used in the optimizat ...

EPFL2009

Process Optimization via Constraints Adaptation

Dominique Bonvin, Alejandro Gabriel Marchetti, Benoît Chachuat

In the framework of real-time optimization, measurement-based schemes have been developed to deal with plant-model mismatch and process variations. These schemes differ in how the feedback information from the plant is used to adapt the inputs. A recent id ...

2008

Real-Time Optimization via Adaptation and Control of the Constraints

Dominique Bonvin, Alejandro Gabriel Marchetti, Benoît Chachuat

In the framework of real-time optimization, measurements are used to compensate for effects of uncertainty. The main approach uses measurements to update the parameters of a process model. In contrast, the constraint-adaptation scheme uses the measurements ...

2008

Batch process optimization via run-to-run constraints adaptation

Dominique Bonvin, Alejandro Gabriel Marchetti, Benoît Chachuat

In the batch process industry, the available models carry a large amount of uncertainty and can seldom be used to directly optimize real processes. Several measurement-based optimization methods have been proposed to deal with model mismatch and process di ...

2007

Real-time optimization of continuous processes via constraints adaptation

Dominique Bonvin, Alejandro Gabriel Marchetti, Benoît Chachuat

In the framework of process optimization, measurements can be used to compensate for the effect of uncertainty. The method studied in this paper combines a process model and measurements to iteratively improve the operation of continuous processes. Unlike ...

2007

Scale-up of batch processes via decentralized control

Michael Amrhein, Dominique Bonvin, Alejandro Gabriel Marchetti, Benoît Chachuat

The economic environment in the specialty chemicals industry requires short times to market and thus the ability to develop new products and processes very rapidly. This, in turn, calls for large scale-ups from laboratory to production. Due to scale-relate ...

2006

Evaluation of Input Parameterization for Batch Process Optimization

Dominique Bonvin, Carsten Welz, Alejandro Gabriel Marchetti

For the optimization of dynamic systems, it is customary to use measurements to combat the effect of uncertainty. In this context, an approach that consists of tracking the necessary conditions of optimality is gaining in popularity. The approach relies st ...

2006

Validation of a Solution Model for the Optimization of a Binary Batch Distillation Column

Dominique Bonvin, Carsten Welz, Alejandro Gabriel Marchetti

2005

Validation du modèle de la solution pour l’optimisation d’une colonne de distillation réactive

Dominique Bonvin, Alejandro Gabriel Marchetti

2005

Measurement-based Run-to-run Optimization of a Batch Reaction-distillation system

Dominique Bonvin, Alejandro Gabriel Marchetti

Recently, measurement-based optimization schemes have been developed to deal with uncertainty and process variations. One of the methods therein, labeled NCO tracking, relies on appropriate parameterization of the input profiles and adjusts the correspondi ...

2005

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