This article proposes direct and indirect model reference adaptive control strategies for
multivariable piecewise affine systems, which constitute a popular tool to model hybrid …

Switching linear models can be used to represent the behavior of hybrid, time‐varying, and
nonlinear systems, while generally providing a satisfactory trade‐off between accuracy and …

How to efficiently identify multiple-input multiple-output (MIMO) linear parameter-varying
(LPV) discrete-time state-space (SS) models with affine dependence on the scheduling …

We present a Kalman-style realization theory for linear parameter-varying state-space
representations whose matrices depend on the scheduling variables in an affine way …

Today, the need to increase efficiency and performance of dynamical systems leads to
innovative control solutions that rely on accurate representations of the underlying system …

Piecewise affine systems constitute a popular framework for the approximation of non-linear
systems and the modelling of hybrid systems. This paper addresses the recursive subsystem …

The paper presents realization theory of discrete-time linear switched systems. We present
necessary and sufficient conditions for an input–output map to admit a discrete-time linear …

When using standard learning techniques for uncertainty approximation, persistently
exciting inputs are necessary in order to achieve good parameter estimation. It has been …

Piecewise affine (PWA) regression is a supervised learning method which aims at
estimating, from a set of training data, a PWA map approximating the relationship between a …

Concurrent Learning has been previously used in continuous-time uncertainty estimation
problems and adaptive control to solve the parameter identification problem without …