Publications by Dominique Bonvin

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Latent-variable calibrations using principal component regression and partial least-squares regression are often compromised by drift such as systematic disturbances and offsets. This paper presents a two-step framework that facilitates the evaluation and ...

This presentation discusses real-time optimization (RTO) strategies for improving process performance in the presence of uncertainty in the form of plant-model mismatch, drifts and disturbances. RTO typically uses a plant model to compute optimal inputs. In the presence of uncertainty, selected model parameters can be estimated and the updated model used for optimization. Although very intuitive, this two-step approach suffers from the fact that the model is almost invariably inadequate, which prevents from

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 extended to solve the disturbance rejection problem. The idea is to tune the controller parameters such that the closed-loop output be uncorrelated with the disturbance signal. Since perfect decorrelation between the closed-loop output and the disturbance signal is not attainable in the restricted-complexi

Optimal operating conditions for a process plant are typically obtained via model based optimization. However, due to modeling errors, the operating conditions found are often sub-optimal or, worse, they can violate critical process constraints. Hence, mod ...

In real-time optimization, enforcing the constraints that need to be active is important for optimality. In fact, it has been established in the context of parametric variations that, if these constraints are not satisfied, the optimality loss would be O($ ...

The desire to operate chemical processes in a safe and economically optimal way has motivated the development of so-called real-time optimization (RTO) methods [1]. For continuous processes, these methods aim to compute safe and optimal steady-state set ...

This paper proposes a set of distributed real-time optimisation schemes for the steady-state optimisation of parametrically and structurally uncertain systems that are composed of multiple interconnected subsystems. These schemes are derived in the framewo ...

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 ...

This paper gives an overview on the theoretical results of recently developed algorithms for iterative controller tuning based on the correlation approach. The basic idea is to decorrelate the output error between the achieved and designed closed-loop systems by iteratively tuning the controller parameters. Two different approaches are investigated. In the first one, a correlation equation involving a vector of instrumental variables is solved using the stochastic approximation method. It is shown that, wit

Economic model predictive control formulations that combine online optimizing control with offset-free methodologies such as modifier adaptation have been proposed recently. These new algorithms are able to achieve asymptotic optimal performance despite th ...

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

The concept of reaction invariants is extended to include flow invariants of chemical-reaction systems with inlet and outlet streams. A transformation to normal form is introduced that allows the separation of (1) the evolution of the independent reactions, (2) the influence of inlet streams, and (3) the behavior of the reaction and flow invariants. In the light of this transformation to normal form, model reduction, state accessibility, state reconstruction, and feedback linearizability are analyzed.

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 ...

This paper presents a data-driven controller tuning method that includes a set of constraints for ensuring closed-loop stability. The approach requires a single experiment and can also be applied to nonminimum-phase or unstable systems. The tuning scheme u ...

This paper deals with the identification of reaction and mass-transfer rates from concentrations measured in gas-liquid reaction systems. It is assumed that the reactions take place in the liquid bulk only. The identification proceeds in two steps: (i) est ...

This paper considers a helicopter-like setup called the Toycopter. Its particularities reside first in the fact that the toycopter motion is constrained to remain on a sphere and second in the use of a variable rotational speed of the propellers to vary th ...

This paper is concerned with input adaptation in dynamic processes in order to guarantee feasible and optimal operation despite the presence of uncertainty. For optimal control problems having mixed control-state constraints, two sets of directions can be ...

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 ...

Dominique Bonvin

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Framework for explicit drift correction in multivariate calibration models

Real-Time Optimization  in the Presence of Uncertainty

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

Real-Time Optimization in the Presence of Uncertainty

Adaptation strategies for tracking constraints under plant-model mismatch

How Important is the Detection of Changes in Active Constraints in Real-Time Optimization?

Distributed Modifier-Adaptation Schemes for the Real-Time Optimization of Interconnected Systems in the Presence of Structural Plant-Model Mismatch

Distributed modifier-adaptation schemes for the real-time optimisation of uncertain interconnected systems

Modifier-Adaptation Methodology for Real-Time Optimization

Iterative Correlation-Based Controller Tuning

Estimation technique for offset-free economic MPC based on modifier adaptation

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

Reaction and Flow Variants/Invariants in Chemical Reaction Systems with Inlet and Outlet Streams

Real-Time Optimization for Kites

Data-driven model reference control with asymptotically guaranteed stability

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

Identification of reaction and mass-transfer rates in gas-liquid reaction systems

Control of the Toycopter using a Flat Approximation

Selective Input Adaptation in Parametric Optimal Control Problems with Path Constraints

Modifier adaptation with guaranteed feasibility in the presence of gradient uncertainty