Publications by Grégory François

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Solid Oxide Fuel Cells (SOFC) are energy conversion devices that produce electrical energy via the reaction of a fuel with an oxidant. Although SOFCs have become credible alternatives to non-renewable energy sources, efforts are still needed to extend their applicability to a broader scope of applications, such as domestic appliances. SOFCs are typically operated continuously and are characterized by the presence of stringent operating constraints. Particularly, violating the constraint on the cell potentia

The steady advances of computational methods make model-based optimization an increasingly attractive method for process improvement. Unfortunately, the available models are often inaccurate. The traditional remedy is to update the model parameters, but th ...

Lower and upper bounds for a given function are important in many mathematical and engineering contexts, where they often serve as a base for both analysis and application. In this short paper, we derive piecewise linear and quadratic bounds that are stated in terms of the Lipschitz constants of the function and the Lipschitz constants of its partial derivatives, and serve to bound the function's evolution over a compact set. While the results follow from basic mathematical principles and are certainly not

In practice, the quest for the optimal operation of energy systems is complicated by the simultaneous presence of operating constraints, among which the need for producing the power required by the user, and of uncertainty. The latter concept incorporates ...

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 ...

Obtaining a reliable gradient estimate for an unknown function when given only its discrete measurements is a common problem in many engineering disciplines. While there are many approaches to obtaining an estimate of a gradient, obtaining lower and upper ...

Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. The users can query the cloud data, paying the price for the infrastructure they use. Cloud management nece ...

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 ...

Solid oxide fuel cell (SOFC) technology is of great potential for efficient combined heat and power (CHP) generation with low overall emissions. To ensure safe and efficient operations of μ-CHP SOFC systems, appropriate control and optimization methods are required. This is generally achieved by using model-based optimization techniques, whereby operating conditions that maximize efficiency and ensure constraint satisfaction are sought. However, mismatch or disturbances always exist between a 'plant' (actua

This document summarizes the author’s research activities since 1999. They mainly focus on the modelling, the control and the optimization of processes and contributed to the development of real-time optimization methods (RTO), that is, process optimization methods that are capable of driving a real process to optimal performances despite uncertainty, modeling errors and process disturbances. The main philosophy of these methods is to use available process measurement to correct the nominal model-based inpu

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 ...

Real-time optimization (RTO) methods use measurements to offset the effect of uncertainty and drive the plant to optimality. RTO schemes differ in the way measurements are incorporated in the optimization framework. Explicit RTO schemes solve a static opti ...

The aim of this paper is to present a global approach to dynamic optimization of batch emulsion polymerization reactors using a stochastic optimizer. The objective is to minimize the final batch time with constraints on the final conversion and molecular w ...

The idea of iterative process optimization based on collected output measurements, or "real-time optimization" (RTO), has gained much prominence in recent decades, with many RTO algorithms being proposed, researched, and developed. While the essential goal of these schemes is to drive the process to its true optimal conditions without violating any safety-critical, or "hard", constraints, no generalized, unified approach for guaranteeing this behavior exists. In this two-part paper, we propose an implementa

Over the past decade, a large number of academics and start-ups have devoted them- selves to developing kites, or airplanes on tethers, as a renewable energy source. Determining the trajectories the kite should follow is a modeling and optimization challen ...

Run-to-run control is a technique that exploits the repetitive nature of processes to iteratively adjust the inputs and drive the run-end outputs to their reference values. It can be used to control both static and finite-time dynamic systems. Although the ...

The optimal operation of a solid oxide fuel cell stack is addressed in this paper. Real-time optimization, performed at a slow time scale via constraint adaptation, is used to account for uncertainty and degradation eﬀects, while model-predictive control i ...

This chapter presents recent developments in the field of process optimization. In the presence of uncertainty in the form of plant-model mismatch and process disturbances, the standard model-based optimization techniques might not achieve optimality for the real process or, worse, they might violate some of the process constraints. To avoid constraints violations, a potentially large amount of conservatism is generally introduced, thus leading to sub-optimal performance. Fortunately, process measurements c

Grégory François

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Model-Predictive Control of an Experimental Solid Oxide Fuel Cell Stack

A Directional Modifier-Adaptation Algorithm for Real-Time Optimization

On linear and quadratic Lipschitz bounds for twice continuously differentiable functions

Real-Time Optimization: Optimizing the Operation of Energy Systems in the Presence of Uncertainty and Disturbances

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

From Discrete Measurements to Bounded Gradient Estimates: A Look at Some Regularizing Structures

Optimal service pricing for a cloud cache

Use of Transient Measurements for Static Real-Time Optimization

Modeling and real-time optimization of a μ-CHP SOFC system

Optimisation en Temps Réel: Optimiser les Performances des Procédés Chimiques malgré l’Incertitude et les Erreurs de Modélisation

Modifier Adaptation for Constrained Closed-Loop Systems

Use of Transient Measurements for the Optimization of Steady-State Performance via Modifier Adaptation

Optimal service pricing for a cloud cache

Dynamic optimization of batch emulsion polymerization using simulated annealing

Sufficient Conditions for Feasibility and Optimality of Real-Time Optimization Schemes - I. Theoretical Foundations

Real-Time Optimization for Kites

Sufficient Conditions for Feasibility and Optimality of Real-Time Optimization Schemes - II. Implementation Issues

A Globally Convergent Algorithm for the Run-to-Run Control of Systems with Sector Nonlinearities

Two-Layered Real-Time Optimization of a Solid Oxide Fuel Cell Stack

Measurement-based Real-Time Optimization of Chemical Processes