Abstract The framework of Linear Parameter Varying (LPV) systems concerns linear
dynamical systems whose state-space representations depend on exogenous nonstationary …

Abstract The Expectation Maximization (EM) algorithm has been widely used for parameter
estimation in data-driven process identification. EM is an algorithm for maximum likelihood …

This book is an introduction to machine learning control (MLC), a surprisingly simple model-
free methodology to tame complex nonlinear systems. These systems are assumed to be …

This paper provides a survey of results in linear parameter-varying (LPV) control that have
been validated by experiments and/or high-fidelity simulations. The LPV controller synthesis …

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 …

Modern wind turbines generally operate at variable speed in order to maximise the
conversion efficiency below rated power and to reduce loading on the drive-train. In …

Gain scheduling for nonlinear controller design is described in terms of general features of
the approach and in terms of early examples of applications in flight control and automotive …

This paper is concerned with the design of gain-scheduled controllers with guaranteed H∞
performance for a class of linear parameter-varying (LPV) plants. Here the plant state-space …

An important class of linear time-varying systems consists of plants where the state-space
matrices are fixed functions of some time-varying physical parameters/spl theta/. Small gain …

Gain scheduling has proven to be a successful design methodology in many engineering
applications. In the absence of a sound theoretical analysis, these designs come with no …