In this paper, we describe POP, a MATLAB toolbox for parametric optimization. It features (a)
efficient implementations of multiparametric programming problem solvers for …

This paper presents a novel real-time implementation of linear model predictive control
(MPC) schemes based on region-less explicit MPC (RL-EMPC). RL-EMPC is a recently …

This paper introduces zonoLAB, a MATLAB-based toolbox for set-based control system
analysis using the hybrid zonotope set representation. Hybrid zonotopes have proven to be …

Tunability is a major obstacle in the creation and subsequent application of the explicit
model predictive control (MPC). The main bottleneck lies in the need to reconstruct the …

Abstract Explicit Model Predictive Control (MPC) is an effective alternative to reduce the on-
line computational demand of traditional MPC. The idea of explicit MPC is to pre-compute …

Model Predictive Control (MPC) is a method to control nonlinear systems with guaranteed
stability and constraint satisfaction but suffers from high computation times. Approximate …

The real-time implementation of the explicit MPC suffers from the evaluation of the,
potentially large, lookup table. The paper revisits the original approach and presents an …

This paper describes a real-time multi-objective predictive control strategy for the wheelchair
ergometer platform, which allows simulating the manual wheelchair (MWC) propulsion in …

Hydrogen is a great energy vector to deal with the renewable energy integration. Indeed,
use renewable energies to produce electrolytic hydrogen with water electrolysis and then …

The industrial implementation of the model predictive control (MPC) is driven by the
necessity to design, tune, and validate the constructed control policy. We present a novel …