Smart electric vehicles (EVs) are attractive because of their clean, zero-emission, low impact
on the environment whilst providing a safer and smoother riding experience. To provide the …

In this article, we propose a novel framework for approximating the MPC policy for linear
parameter-varying systems using supervised learning. Our learning scheme guarantees …

In this paper, we propose a novel framework for approximating the explicit MPC law for
linear parameter-varying systems using supervised learning. In contrast to most existing …

This paper proposes an Adaptive Robust Model Predictive Control strategy for lateral control
in lane keeping problems, where we continuously learn an unknown, but constant steering …

This paper proposes an Adaptive Learning Model Predictive Control strategy for uncertain
constrained linear systems performing iterative tasks. The additive uncertainty is modeled as …

In recent years, driving simulators have been widely used by automotive manufacturers and
researchers in human-in-the-loop experiments, because they can reduce time and …

Autonomous driving is an old desire of mankind. The main purpose of this article is to
present an autonomous lane changing method, that enables fully automated lane changing …

This paper proposes an adaptive stochastic Model Predictive Control (MPC) strategy for
stable linear time invariant systems in the presence of bounded disturbances. We consider …

Assessing passenger cars' dynamic performance is a critical aspect for car industries, due to
its impact on the overall vehicle safety evaluation and the subjective nature of the involved …

Electric power steering systems have been used to generate assist torque for driver comfort.
This study makes use of the functionality of electric power steering systems for autonomous …