Based on the extension of the behavioral theory and the Fundamental Lemma for Linear
Parameter-Varying (LPV) systems, this paper introduces a Data-driven Predictive Control …

In the literature, a recent debate has been brought up regarding how linear time-invariant
systems can be represented by trajectories features. That is, how a single input–output (IO) …

We derive novel methods that allow to synthesize LPV state-feedback controllers directly
from a single sequence of data and guarantee stability and performance of the closed-loop …

In this article, we derive direct data-driven dissipativity analysis methods for linear parameter-
varying (LPV) systems using a single sequence of input-scheduling-output data. By means …

The Linear Parameter-Varying (LPV) framework provides a modeling and control design
toolchain to address nonlinear (NL) system behavior via linear surrogate models. Despite …

In this paper, battery overpotential model identification approaches based on local and
global Linear Parameter-Varying (LPV) input–output models are developed. Key features …

This monograph presents for the first time a unified synthesis on how to design robust and
predictive control approaches for (discrete-time) Linear Parameter Varying (LPV) systems. In …

Selecting the minimum number of linear models required to characterize a nonlinear
dynamic system in the local approach to linear parameter varying (LPV) model identification …

Models are the key to model-based control strategies. However, due to the nonlinear and
time-varying nature of industrial processes, plant–model mismatches are inevitable …

This paper considers the equilibrium‐free stability and performance analysis of discrete‐
time nonlinear systems. Two types of equilibrium‐free notions are considered. Namely, the …