This paper presents an overview of research on data-driven modeling and learningbased
control of nonlinear systems in linear parameter-varying (LPV) framework. Data-driven …

This paper proposes a novel data classification framework, combining sparse auto-encoders
(SAEs) and a post-processing system consisting of a linear system model relying on Particle …

In this paper, a robust controller based on Linear Parameter Varying (LPV) model with
scheduling variable reduction is applied for a lane-keeping system. On a curved road …

In this paper, the existing Scheduling Dimension Reduction (SDR) methods for Linear
Parameter-Varying (LPV) models are reviewed and a Deep Neural Network (DNN) …

In our society, we are constantly improving systems and processes across various domains
to satisfy increasingly higher performance requirements, for example in terms of speed …

The control of nonlinear large-scale dynamical models such as the incompressible Navier-
Stokes equations is a challenging task. The computational challenges in the controller …

This paper presents an overview and comparative study of the state of the art in State-Order
Reduction (SOR) and Scheduling Dimension Reduction (SDR) for Linear Parameter …

Obtaining models that can be used for flight control is of outmost importance to ensure
reliable guidance and navigation of spacecrafts, like a Generic Parafoil Return Vehicle …

This paper presents a robust controller using a Linear Parameter Varying (LPV) model of a
lane-keeping system with parameter reduction. Both varying vehicle speed and roll motion …

In this paper, the problem of automated generation of linear parameter-varying (LPV) state-
space models is addressed. A deep neural network (DNN) is developed to embed the …