Publications by Alejandro Gabriel Marchetti

Modifier Adaptation as a Feedback Control Scheme

Dominique Bonvin, Alejandro Gabriel Marchetti, Sean Costello, Tafarel de Avila Ferreira

As a real-time optimization technique, modifier adaptation (MA) has gained much significance in recent years. This is mainly due to the fact that MA can deal explicitly with structural plant-model mismatch and unknown disturbances. MA is an iterative techn ...

AMER CHEMICAL SOC2020

A note on efficient computation of privileged directions in modifier adaptation

Dominique Bonvin, Alejandro Gabriel Marchetti, Martand Singhal, Timm Faulwasser

In the presence of plant-model mismatch, the estimation of plant gradients is key to the performance of measurement-based iterative optimization schemes. However, gradient estimation requires time-consuming experiments, wherein the plant is sequentially pe ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Real-time optimization of load sharing for gas compressors in the presence of uncertainty

Dominique Bonvin, Alejandro Gabriel Marchetti, Timm Faulwasser, Predrag Milosavljevic

This paper investigates the problem of load-sharing optimization of gas compressors in the presence of uncertainty. The objective is to operate a set of compressor units in an energy-efficient way, while at the same time meeting a varying load demand. The ...

ELSEVIER SCI LTD2020

Analysis of output modifier adaptation for real-time optimization

Dominique Bonvin, Alejandro Gabriel Marchetti

In the context of real-time optimization, modifier-adaptation schemes update the model-based optimization problem by adding first-order correction terms to the cost and constraint functions of the optimization problem. This guarantees meeting the plant fir ...

PERGAMON-ELSEVIER SCIENCE LTD2019

Real-time optimization of an experimental solid-oxide fuel-cell system

Dominique Bonvin, Christophe Salzmann, Jan Van Herle, Zacharie Wuillemin, Alejandro Gabriel Marchetti

There still exists a large gap between simulation work and industrial applications in the context of control and optimization of solid-oxide fuel-cell (SOFC) systems. In an effort to bridge this gap, this study describes the experimental implementation of ...

ELSEVIER SCIENCE BV2019

Fast RTO Applied to a Commercial SOFC System

Dominique Bonvin, Zacharie Wuillemin, Alejandro Gabriel Marchetti

The experimental implementation of real-time optimization (RTO) to a commercial solid-oxide fuel-cell (SOFC) system is reported in this paper. The goal of RTO is to maximize the system efficiency at steady state subject to several operating constraints. Th ...

ELSEVIER SCIENCE BV2019

A feasible-side globally convergent modifier-adaptation scheme

Dominique Bonvin, Alejandro Gabriel Marchetti, Timm Faulwasser

In the context of static real-time optimization (RTO) of uncertain plants, the standard modifier-adaptation scheme consists in adding first-order correction terms to the cost and constraint functions of a model based optimization problem. If the algorithm ...

Elsevier Sci Ltd2017

Modifier adaptation with guaranteed feasibility in the presence of gradient uncertainty

Dominique Bonvin, Alejandro Gabriel Marchetti, Martand Singhal, Timm Faulwasser

In the context of real-time optimization, modifier-adaptation schemes use estimates of the plant gradients to achieve plant optimality despite plant-model mismatch. Plant feasibility is guaranteed upon convergence, but not at the successive operating point ...

Pergamon-Elsevier Science Ltd2017

Use of Transient Measurements for Static Real-Time Optimization

Dominique Bonvin, Grégory François, Alejandro Gabriel Marchetti, Tafarel de Avila Ferreira

Modifier adaptation (MA) is a real-time optimization (RTO) method characterized by its ability to enforce plant optimality upon convergence despite the presence of model uncertainty. The approach is based on correcting the available model using gradient es ...

2017

Improved Directional Derivatives for Modifier-Adaptation Schemes

Dominique Bonvin, Alejandro Gabriel Marchetti, Martand Singhal, Timm Faulwasser

The modifier-adaptation methodology enables real-time optimization (RTO) of plant operation in the presence of considerable plant-model mismatch. It requires the estimation of plant gradients. Obtaining these gradients is expensive as it involves potential ...

2017

Real-Time Optimization Based on Adaptation of Surrogate Models

Dominique Bonvin, Alejandro Gabriel Marchetti, Martand Singhal, Timm Faulwasser

Recently, different real-time optimization (RTO) schemes that guarantee feasibility of all RTO iterates and monotonic convergence to the optimal plant operating point have been proposed. However, simulations reveal that these schemes converge very slowly t ...

Elsevier Science Bv2016

Time-Optimal Path-Following Operation in the Presence of Uncertainty

Dominique Bonvin, Alejandro Gabriel Marchetti, Timm Faulwasser, Predrag Milosavljevic

Path-following tasks, which refer to dynamic motion planning along pre-specified geometric references, are frequently encountered in applications such as milling, robot-supported measurements, and trajectory planning for autonomous vehicles. Different conv ...

Ieee2016

Economic plant-wide control design with backoff estimations using internal model control

Alejandro Gabriel Marchetti

Economic optimal operation typically involves operating as close as possible to the active constraints. However, in the presence of disturbances it is necessary to back-off from the constraints in order to avoid violating them. The backoff approach aims at ...

Elsevier Sci Ltd2016

Optimal Load Sharing of Parallel Compressors via Modifier Adaptation

Dominique Bonvin, Alejandro Gabriel Marchetti, Timm Faulwasser, Predrag Milosavljevic

2016

Modifier Adaptation for Real-Time Optimization -- Methods and Applications

Dominique Bonvin, Grégory François, Alejandro Gabriel Marchetti, Timm Faulwasser

This paper presents an overview of the recent developments of modifier-adaptationschemes for real-time optimization of uncertain processes. These schemes have the ability to reach plant optimality upon convergence despite the presence of structural plant-m ...

MDPI2016

On the Use of Transient Information for Static Real-Time Optimization

Dominique Bonvin, Grégory François, Alejandro Gabriel Marchetti

Optimal operation of chemical processes is key for meeting productivity, quality, safety and environmental objectives. Both model-based and data-driven schemes are used to compute optimal operating conditions [1]: - The model-based techniques are intu ...

2015

Modifier Adaptation for Constrained Closed-Loop Systems

Dominique Bonvin, Grégory François, Alejandro Gabriel Marchetti, Sean Costello

The steady advance of computational methods makes model-based optimization an increasingly attractive method for process improvement. Unfortunately, the available models are often inaccurate. An iterative optimization method called "modifier adaptation" ov ...

2014

Robust Real-Time Optimization of a Solid Oxide Fuel Cell Stack

Dominique Bonvin, Jan Van Herle, Zacharie Wuillemin, Arata Nakajo, Alejandro Gabriel Marchetti, Benoît Chachuat, Leonidas Tsikonis

On-line control and optimization can improve the eﬃciency of fuel cell systems whilst simultaneously ensuring that the operation remains within a safe region. Also, fuel cells are subject to frequent variations in their power demand. This paper investigate ...

2011

A Dual Modifier-Adaptation Approach for Real-Time Optimization

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 plant-model mismatch problem. Unlike the two-step schemes combining parameter estimation and optimization, the modifier-adaptation approach does no ...

Elsevier2010

Modifier-Adaptation Methodology for Real-Time Optimization

Dominique Bonvin, Alejandro Gabriel Marchetti

The ability of a model-based real-time optimization scheme to converge to the plant optimum relies on the ability of the underlying process model to predict the plant's necessary conditions of optimality (NCO). These include the values and gradients of the ...

2009