In this contribution we discuss the modeling and model reduction framework known as the
Loewner framework. This is a data-driven approach, applicable to large-scale systems …

In this paper, we address stability enforcement for reduced-order models computed from
data (transfer function measurements). Two data-driven methods based on interpolation will …

In this article, a direct data-driven design method, based on frequency-domain data, is
proposed. The identification of the plant is skipped and the controller is designed directly …

Linear dynamical models play an important role in many engineering fields, including
simulation, analysis, optimization and control of complex systems and processes. This role is …

Water level control in open channels used for hydroelectric production is addressed in this
paper. In order to use classical methods of controller design, a new reduced order model …

The design and assessment of a two degree of freedom gust load allevi-ation control system
for a business jet aircraft is presented in this paper. The two degrees of freedom are a …

In this paper a novel approach to design linear disturbance estimators is presented. The
model based design approach relies on advanced nullspace computation techniques and …

In many applications, no physical description of the plant is easily available and the control
law has to be designed on the basis of input-output measurements only. Two control …

In this paper, an algorithm to identify parametric systems with an affine (or polynomial)
parameter dependence through the subspace framework is proposed. It stands as an …

The choice of a reference model in data-driven control techniques is a critical step. Indeed, it
should represent the desired closed-loop performances and be achievable by the plant at …