Aerodynamic modeling plays an important role in multiphysics and design problems, in
addition to experiment and numerical simulation, due to its low-dimensional representation …

The efficacy of the multimodel framework (MMF) in modeling and identification of complex,
nonlinear, and uncertain systems has been widely recognized in the literature owing to its …

Through the past 20 years, the framework of Linear Parameter-Varying (LPV) systems has
become a promising system theoretical approach to handle the control of mildly nonlinear …

In this paper, we establish a unified framework for subspace identification (SID) of linear
parameter-varying (LPV) systems to estimate LPV state–space (SS) models in innovation …

This paper is concerned with identification of linear parameter varying (LPV) systems in an
input–output setting with Box–Jenkins (BJ) model structure. Classical linear time invariant …

A common approach for modeling LPV systems is to interpolate between local LTI models,
often obtained by system identification methods. We study the results of interpolating in …

This paper addresses the problems of robust global identification and fast-rate output
estimation for linear parameter varying (LPV) dual-rate systems with output measurements …

In this paper, we propose a solution to the problem of adaptive control and parameter
estimation in systems with unstable target dynamics. Models of uncertainties are allowed to …

The objective of this paper is to show how experimentally basedmodelling can be used for
designing Linear Parametrically Varying (LPV) controllers. As a test system we use an …

A global model structure is developed for parametrization and identification of a general
class of Linear Parameter-Varying (LPV) systems. By using a fixed orthonormal basis …