Model predictive control (MPC) has established itself as a promising control methodology in
power electronics. This survey paper highlights the most relevant MPC techniques for power …

Nonlinear model predictive control (NMPC) allows one to explicitly treat nonlinear dynamics
and constraints. To apply NMPC in real time on embedded hardware, online algorithms as …

We present CasADi, an open-source software framework for numerical optimization. CasADi
is a general-purpose tool that can be used to model and solve optimization problems with a …

This paper presents the acados software package, a collection of solvers for fast embedded
optimization intended for fast embedded applications. Its interfaces to higher-level …

This paper introduces HPIPM, a high-performance framework for quadratic programming
(QP), designed to provide building blocks to efficiently and reliably solve model predictive …

Linear model predictive control (MPC) can be currently deployed at outstanding speeds,
thanks to recent progress in algorithms for solving online the underlying structured quadratic …

The Multi-Parametric Toolbox is a collection of algorithms for modeling, control, analysis,
and deployment of constrained optimal controllers developed under Matlab. It features a …

This paper describes autonomous racing of RC race cars based on mathematical
optimization. Using a dynamical model of the vehicle, control inputs are computed by …

In this paper, we describe the embedded conic solver (ECOS), an interior-point solver for
second-order cone programming (SOCP) designed specifically for embedded applications …

In this original book on model predictive control (MPC) for power electronics, the focus is put
on high-power applications with multilevel converters operating at switching frequencies …