Dynamical systems see widespread use in natural sciences like physics, biology, and
chemistry, as well as engineering disciplines such as circuit analysis, computational fluid …

The aim of this paper is to review and to propose a classification of a number of
decentralized, distributed and hierarchical control architectures for large scale systems …

Dynamic locomotion in rough terrain requires accurate foot placement, collision avoidance,
and planning of the underactuated dynamics of the system. Reliably optimizing for such …

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

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 …

In this chapter, we introduce the nonlinear model predictive control algorithm in a rigorous
way. We start by defining a basic NMPC algorithm for constant reference and continue by …

Fast and safe navigation of dynamical systems through a priori unknown cluttered
environments is vital to many applications of autonomous systems. However, trajectory …

Real-time implementation of optimisation-based control and trajectory planning can be very
challenging for nonlinear systems. As a result, if an implementation based on a fixed …

In this paper the software environment and algorithm collection ACADO Toolkit is presented,
which implements tools for automatic control and dynamic optimization. It provides a general …