Thanks to their road safety potential, automated vehicles are rapidly becoming a reality. In
the last decade, automated driving has been the focus of intensive automotive engineering …

Model predictive control (MPC) has demonstrated exceptional success for the high-
performance control of complex systems. The conceptual simplicity of MPC as well as its …

We propose a robust data-driven model predictive control (MPC) scheme to control linear
time-invariant systems. The scheme uses an implicit model description based on behavioral …

Hybrid Electric Vehicles (HEVs) have been proven to be a promising solution to
environmental pollution and fuel savings. The benefit of the solution is generally realized as …

The adapting of lateral deviation during the change of road curvature with less error, system
settling time, and overshoot is the main challenge against the steering angle control of …

As one of the most promising large-scale energy storage technologies, vanadium redox flow
battery (VRFB) has been installed globally and integrated with microgrids (MGs), renewable …

A learning model predictive controller for iterative tasks is presented. The controller is
reference-free and is able to improve its performance by learning from previous iterations. A …

CONTROLLER design is more troublesome in aerospace systems due to, inter alia, diversity
of mission platforms, convoluted nonlinear dynamics, predominantly strict mission and …

In this article, we present a nonlinear robust model predictive control (MPC) framework for
general (state and input dependent) disturbances. This approach uses an online …

This paper proposes a novel data-driven robust optimization framework that leverages the
power of machine learning and big data analytics for decision-making under uncertainty. By …