Towards a modular software package for embedded optimization. Issue 20 (2018)

• Record Type: Journal Article
• Authors: Verschueren, Robin; Frison, Gianluca; Kouzoupis, Dimitris; van Duijkeren, Niels; Zanelli, Andrea; Quirynen, Rien; Diehl, Moritz
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 20(2018)
• Page Start: 374
• Page End: 380
• Publication Date: 2018
• Subjects: Nonlinear Model Predictive Control -- Embedded Optimization -- Software; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.11.062
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: 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 on computational efficiency. Its modular structure makes it useful for rapid prototyping, i.e. designing a control algorithm by putting together different algorithmic components that are readily connected and interchanged. The usefulness of the software is demonstrated with a closed-loop simulation experiment of an inverted pendulum, which shows acados attaining sub-millisecond computation times per iteration. Furthermore, we showcase a new algorithmic idea in the context of embedded nonlinear model predictive control (NMPC), namely sequential convex quadratic programming (SCQP), along with an efficient implementation of it.