acados

Fast and embedded solvers for nonlinear optimal control.

• acados source code is hosted on Github. Contributions via pull requests are welcome!

• acados has a discourse based forum.

• acados is mainly developed by the syscop group around Prof. Moritz Diehl, the Systems Control and Optimization Laboratory, at the University of Freiburg.

About acados

acados is a software package providing fast and embedded solvers for nonlinear optimal control. Problems can be conveniently formulated using the CasADi symbolic framework and the high-level acados interfaces.

acados provides a collection of computationally efficient building blocks tailored to optimal control structured problems, most prominently optimal control problems (OCP) and moving horizon estimation (MHE) problems. Among others, acados implements:

• modules for the integration of ordinary differential equations (ODE) and differential-algebraic equations (DAE),

• interfaces to state-of-the-art QP solvers like HPIPM, qpOASES, DAQP and OSQP

• (partial) condensing routines, provided by HPIPM

• nonlinear programming solvers for optimal control structured problems

• real-time algorithms, such as the real-time iteration (RTI) and advanced-step real-time iteration (AS-RTI) algorithms

The back-end of acados uses the high-performance linear algebra package BLASFEO, in order to boost computational efficiency for small to medium scale matrices typical of embedded optimization applications. MATLAB, Octave and Python interfaces can be used to conveniently describe optimal control problems and generate self-contained C code that can be readily deployed on embedded platforms.

Problem Formulation

Since acados mainly aims on providing SQP type methods for optimal control, it naturally needs optimal control structured nonlinear programming formulations (OCP-NLP) and quadratic programming (QP) formulations to tackle the subproblems within SQP.

• Optimal control structured NLP (OCP-NLP): The problem formulation targeted by acados OCP solver is stated here.

• QP formulations (dense and OCP structured): acados relies on HPIPM for reformulating QP problems via (partial) condensing and expansion routines. We thus use the flexible QP formulations from HPIPM for optimal control structured quadratic programming formulation (OCP-QP) and the dense QP formulation. Both problem formulations are documented in the HPIPM guide.

Documentation page overview

Documentation latest build: Oct 18, 2024

• Home
• Citing
  • Publications on advanced acados features
• Installation
  • Linux/Mac
  • Windows 10+ (WSL)
  • Windows (for use with Matlab)
• Other Projects that feature acados
  • Software interfaced with acados
  • Papers featuring acados
• Developer Guide
  • Contributing
  • Memory management in acados
  • Regularization within SQP / SQP-RTI
  • Dense QP solution: Populating dense_qp_out

Interfaces

• Interfaces Overview
• Python Interface
  • Examples
  • Optimal Control Problem description
  • Installation
  • Overview
  • acados OCP solver interface
  • acados integrator interface
  • Builders
  • acados multi-phase OCP
• Matlab + Simulink and Octave Interface
  • Getting started
  • Export environment variables
  • Interface structure
  • Options documentation
  • Simulink
  • Setup CasADi
• Embedded Workflow
  • dSPACE DS1202
  • dSPACE DS1401 and DS1403