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
andOSQP
(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 onHPIPM
for reformulating QP problems via (partial) condensing and expansion routines. We thus use the flexible QP formulations fromHPIPM
for optimal control structured quadratic programming formulation (OCP-QP) and the dense QP formulation. Both problem formulations are documented in theHPIPM guide
.
Documentation page overview¶
Documentation latest build: May 07, 2024