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 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 …

In the last three decades, the field of computational intelligence has seen a profusion of
population‐based metaheuristics applied to a variety of problems, where they achieved …

A nonlinear MPC framework is presented that is suitable for dynamical systems with
sampling times in the (sub) millisecond range and that allows for an efficient implementation …

Over the past 20 years, great strides have been made in the real-time implementation of
linear MPC on FPGA devices. Starting from initial work, which demonstrated the benefits of …

Abstract We present Optimization Engine (OpEn): an open-source code generation
framework for real-time embedded nonconvex optimization, which implements a novel …

Basic Linear Algebra Subroutines for Embedded Optimization (BLASFEO) is a dense linear
algebra library providing high-performance implementations of BLAS-and LAPACK-like …

In this paper we present acados, a new software package for model predictive control. It
provides a collection of embedded optimization algorithms written in C, with a strong focus …

This paper presents a novel control framework to handle safety-critical control for non-affine
nonlinear systems. The proposed control development is considered to deal with safety …

This work proposes a Model Predictive Control (MPC) policy for simultaneous station
kee** and momentum management of a low-thrust nadir-pointing satellite in geostationary …