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Reference and command governors are add-on control schemes which enforce state and
control constraints on pre-stabilized systems by modifying, whenever necessary, the …

We show that artificial neural networks with rectifier units as activation functions can exactly
represent the piecewise affine function that results from the formulation of model predictive …

Autonomous marine vehicles (AMVs) have received considerable attention in the past few
decades, mainly because they play essential roles in broad marine applications such as …

This paper presents a method to compute an approximate explicit model predictive control
(MPC) law using neural networks. The optimal MPC control law for constrained linear …

This paper provides an overview of the recent research efforts on the integration of machine
learning and model predictive control under uncertainty. The paper is organized as a …

Because of their complex behavior, wastewater treatment processes (WWTPs) are very
difficult to control. In this paper, the design and implementation of a nonlinear model …

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 …

To facilitate the real-time implementation of nonlinear model predictive control (NMPC), this
paper proposes a deep learning-based NMPC scheme, in which the NMPC law is …

This article proposes an algorithm for solving multivariate regression and classification
problems using piecewise linear predictors over a polyhedral partition of the feature space …