Publications de Dominique Bonvin

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A new nonlinear model is proposed for describing the rela-tionship between the relevant inputs and outputs of a DC-magnetron sputtering system used in a manufacturing line for digital-compact discs and analogous optical data-storage devices. It is shown that the process is inherently discrete, and that it has an inherent transport delay. A control scheme is proposed consisting of a Smith predictor to address the delayed dynamics, and a globally linearizing operator is introduced to address the nonlinear nat

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 ...

An incremental identification approach for determining the kinetics of homogeneous reaction systems from transient concentration measurements has been developed in previous work (Marquardt, W. Chemical Engineering Research and Design 83(A6), 561–573, 2005) ...

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 ...

A numerical algorithm that achieves asymptotic stability for feedback linearizable systems is presented. The nonlinear systems can be represented in various forms that include differential equations, simulated physical models or lookup tables. The proposed ...

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

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 counter. Accordingly, the control and opt ...

SpiderCrane is a three-dimensional crane, whose main particularity lies in the absence of large inertial moving parts. This paper presents experimental results obtained with the novel jet-scheduling control methodology that is based on differential flatnes ...

Improving the productivity of fed-batch filamentous fungal fermentations can be formulated as a dynamic optimization problem. However, numerical optimization based on a nominal process model is typically insufficient when uncertainty in the form of model m ...

Model predictive control (MPC) is a very effective approach to control nonlinear systems, especially when the systems are high dimensional and/or constrained. MPC formulates the problem of input trajectory generation as an optimization problem. However, due to model mismatch and disturbances, frequent re-calculation of the trajectories is typically called for. This paper proposes a two-time-scale control scheme that uses less frequent repeated trajectory generation in a slow loop and time-varying linear fee

Empirical model identification for biological systems is a challenging task due to the combined effects of complex interactions, nonlinear effects, and lack of specific measurements. In this context, several researchers have provided tools for experimental ...

Dynamic Magnetic Resonance Imaging (MRI) with contrast media injection is an important tool to study renal perfusion in humans and animals. The goal of this study is to build classifiers for the automatic classification of a kidney as healthy or pathological. A new algorithm is developed that segments out the cortex from the rest of the kidney including the medulla, the renal pelvic, and the background. The performance of two classifier-types (Soft Independent Method of Class Analogy, SIMCA; Partial Least S

The sensitivity of the unmeasured state variables to the measurements strongly affects the rate of convergence of a state estimation algorithm. To overcome potential observability problems, the approach has been to identify the model parameters so as to re ...

For gas-liquid reaction systems with inlet and outlet streams, this paper proposes a linear transformation to decompose the numbers of moles vector into five distinct parts, namely, the extents of reaction, the extents of mass transfer, the extents of inle ...

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 ...

Real-time data reconciliation of concentration estimates of process analytes and biomass in microbial fermentations is investigated. A Fourier-transform mid-infrared spectrometer predicting the concentrations of process metabolites is used in parallel with ...

Many real-time optimization schemes maximize process performance by performing a model-based optimization. However, due to plant-model mismatch, the model-based solution is often suboptimal. In modifier adaptation, measurements are used to correct the mode ...

The contribution of this article is to propose and experimentally validate an optimizing control strategy for power kites flying crosswind. The control strategy provides both path control (stability) and path optimization (efficiency). The path following part of the controller is capable of robustly following a reference path, despite significant time delays, using position measurements only. The path-optimization part adjusts the reference path in order to maximize line tension. It uses a real-time optimiz

Optimization in the process industry has received a lot of attention in recent years because, in the face of growing competition, it represents a natural choice for reducing production costs, improving product quality, and meeting safety requirements and environmental regulations. Traditionally, the optimal operating conditions are determined based on a model of the process. However, the resulting process operation can be highly sensitive to uncertainty such as model mismatch and process disturbances. This

Dominique Bonvin

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Run-to-Run Control of DC-Sputtering Processes

A quotient method for designing nonlinear controllers

Incremental Identification of Reaction Systems - A Comparison between Rate-based and Extent-based Approaches

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

Numerical algorithm for feedback linearizable systems

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

Measurement-based Real-Time Optimization of Chemical Processes

Control and Optimization of Batch Processes

Jet-Scheduling Control for SpiderCrane: Experimental Results

Run-to-run Optimization of Filamentous Fungal Fermentation

A Two-Time-Scale Control Scheme for Fast Systems

Shape constrained splines as transparent black-box models for bioprocess modeling

Classification of magnetic resonance images from renal perfusion studies of rabbits

Parameter Identification to Enforce Practical Observability of Nonlinear Systems

Extents of Reaction, Mass Transfer and Flow for Gas-Liquid Reaction Systems

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

Data Reconciliation of Concentration Estimates from Mid-Infrared and Dielectric Spectral Measurements for Improved On-Line Monitoring of Bioprocesses

Active Directional Modifier Adaptation with Trust Region - Application to Energy-Harvesting Kites

Real-Time Optimizing Control of an Experimental Crosswind Power Kite

Measurement-based Optimization via NCO Tracking: Challenges and Opportunities