Publications de Dominique Bonvin

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An algorithmic method is proposed to design stabilizing control laws for a class of nonlinear systems that comprises single-input feedback-linearizable systems and a particular set of single-input non feedback-linearizable systems. The method proceeds iter ...

Feedback linearization requires a unique feedback law and a unique diffeomorphism to bring a system to Brunovsk´y normal form. Unfortunately, singularities might arise both in the feedback law and in the diffeomorphism. This paper demonstrates the ability ...

Extent-based incremental identification uses the concept of extents and the integral method of parameter estimation to identify reaction kinetics from concentration measurements. The approach is rather general and can be applied to open both homogeneous an ...

The experimental validation of a real-time optimization (RTO) strategy for the optimal operation of a solid oxide fuel cell (SOFC) stack is reported in this paper. Unlike many existing studies, the RTO approach presented here utilizes the constraint-adapta ...

We consider the real-time optimization of static plants and propose a generalized version of the modifier-adaptation strategy that relies on second-order adaptation of the cost and constraint functions. We show that second-order adaptation allows checking ...

Cable-operated manipulators, also termed cable robots, possess a number of unique properties which make them suitable for tasks involving high payloads, large workspaces, and interacting with dangerous materials. But the fact that cables can only pull the ...

The problem of steering a dynamical system toward optimal steady-state performance is considered. For this purpose, a static optimization problem can be formulated and solved. However, because of uncertainty, the optimal steady-state inputs can rarely be a ...

A correlation-based controller tuning method is proposed for the \Design and optimization of restricted-complexity controllers" benchmark problem. The approach originally proposed for model following is applied to solve the disturbance rejection problem. The idea is to tune the controller parameters such that the closed-loop output be uncorrelated with the measured disturbance. Since perfect decorrelation between the closed-loop output and the disturbance is not attainable with a restricted-complexity contr

Experimental assessment or prediction of plant steady state is important for many applications in the area of modeling and operation of continuous processes. For example, the iterative implementation of static real-time optimization requires reaching stead ...

This paper presents a data-driven controller-tuning algorithm that includes a sufficient condition for closed-loop stability. This stability condition is defined by a set of convex constraints on the Fourier transform of specific auto- and cross-correlatio ...

Challenges in real-time process optimization mainly arise from the inability to build and adapt accurate models for complex physico-chemical processes. This paper surveys different ways of using measurements to compensate for model uncertainty in the conte ...

Dynamic optimization can be used to determine optimal input profiles for dynamic processes. Due to plant-model mismatch and disturbances, the optimal inputs determined through model-based optimization will, in general, not be optimal for the plant. Modifie ...

A batch process is characterized by the repetition of time-varying operations of finite duration. Due to the repetition, there are two independent “time” variables, namely, the run time during a batch and the batch index. Accordingly, the control and optimization objectives can be defined for a given batch or over several batches. This chapter describes the various control and optimization strategies available for the operation of batch processes. These include online and run-to-run control on the one hand,

The performance of a predictive controller is typically poor when the true plant evolution deviates significantly from that predicted by the model. A robust control approach that considers model uncertainty explicitly is then needed. However, it is often d ...

The development of a wide array of process technologies to enable the shift from conventional biological wastewater treatment processes to resource recovery systems is matched by an increasing demand for predictive capabilities. Mathematical models are exc ...

A shortcut model is a low-order model that provides a simplified representation of a complex process, thereby enabling faster and more efficient analysis, design and optimization without the computational intensity of a full-scale model. For continuous dis ...

Real-Time Optimization (RTO) via modifier adaptation is a class of methods for which measurements are used to iteratively adapt the model via input-affine additive terms. The modifier terms correspond to the deviations between the measured and predicted co ...

In practice, the quest for the optimal operation of energy systems is complicated by the presence of operating constraints, which includes the need to produce the power required by the user, and by the need to account for uncertainty. The latter concept in ...

In the framework of process optimization, the use of measurements to compensate the effect of uncertainty has become an active area of research. One of the ideas therein is to enforce optimality by tracking the necessary conditions of optimality (NCO track ...

The mitogen-activated protein kinase (MAPK) cascades are ubiquitous in eukaryotic signal transduction, and these pathways are conserved in cells from yeast to mammals. Metabolic engineering of mammalian cells requires the redesign of the steady-sate and the dynamic responses of signal transduction pathways. Therefore, understanding the design principles of these pathways is a key to success of metabolic engineering for cell culture development and drug target discovery.

Dominique Bonvin

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A Quotient Method for Designing Nonlinear Controllers

Avoiding Feedback-Linearization Singularity Using a Quotient Method -- The Field-Controlled DC Motor Case

Extent-based incremental identification of reaction systems using concentration and calorimetric measurements

Experimental Real-Time Optimization of a Solid Oxide Fuel Cell Stack via Constraint Adaptation

On the Use of Second-Order Modifiers for Real-Time Optimization

Stabilization of a 2D-SpiderCrane Mechanism Using Damping Assignment Passivity-based Control

Equivalence between Neighboring-Extremal Control and Self-Optimizing Control for the Steady-State Optimization of Dynamical Systems

Correlation-Based Tuning of a Restricted-Complexity Controller for an Active Suspension System

Fast Estimation of Plant Steady State, with Application to Static RTO

Data-driven controller tuning with integrated stability constraint

Adaptation Strategies for Real-time Optimization

Modifier Adaptation for Run-to-Run Optimization of Transient Processes

Control and Optimization of Batch Chemical Processes

Robust Predictive Control Based on Neighboring Extremals

Identification of Biokinetic Models Using the Concept of Extents

A shortcut model for batch distillation columns using pertinent effective factors

Use of Convex Model Approximations for Real-Time Optimization via Modifier Adaptation

Application of Real-Time Optimization Methods to Energy Systems in the Presence of Uncertainties and Disturbances

Tracking the Necessary Conditions of Optimality with Changing Set of Active Constraints using a Barrier-Penalty Function

Identification of the Design Principles of Signaling Pathways for Metabolic Engineering