# acados/acados

Fast and embedded solvers for nonlinear optimal control and nonlinear model predictive control

Repository: https://github.com/acados/acados
Canonical: https://ross.abutalabs.com/products/acados
Homepage: https://docs.acados.org
Language: C
License: NOASSERTION
License Family: other
Topics: embedded, optimization, nonlinear, optimal, control, differentiable-programming, high-performance, model-predictive-control, real-time, simulation, solver, moving-horizon-estimation, nonlinear-control, simulink, differential-dynamic-programming, differentiable-optimization, differentiable-model-predictive-control, optimal-control
Last push: 2026-08-12T14:08:23+00:00

## Health v2 (maintenance only)
Score: 93/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 97, release rhythm 84, longevity 100
- inputs: {"age_days": 3802, "days_push": 21, "days_rel": 27, "gap_med": 36.0, "n_releases_24m": 13}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1450, forks 359 (observed 2026-08-28T04:04:45.653295+00:00)

## What it is
acados is a modular C library providing fast embedded solvers for nonlinear optimal control problems, designed for real-time applications like model predictive control (MPC) and moving horizon estimation (MHE). It offers high-level interfaces for Python, MATLAB, Octave, and Simulink, and can generate self-contained C code for deployment on embedded systems.

## Use cases
- solve nonlinear model predictive control problems in real time
- implement moving horizon estimation for state and parameter estimation
- deploy an MPC solver as generated C code on an embedded system
- simulate ODE and DAE systems with sensitivity propagation
- embed a differentiable NLP solver as a layer in a machine learning pipeline
- formulate multi-phase optimal control problems
- prototype MPC controllers from Python or MATLAB/Simulink

## When to choose
- you need fast, real-time nonlinear MPC or MHE with millisecond solve times
- you target embedded hardware or high-frequency control loops
- you want code-generated, self-contained solvers deployable without heavy dependencies
- you need solution sensitivities for reinforcement learning or gradient-based tuning
- you work with ODEs and DAEs and need efficient integrators with first- and second-order sensitivities

## When to avoid
- you only need to solve general-purpose NLPs without optimal control structure (use IPOPT or similar)
- you need a pure high-level Python solver without compiling C code
- your problem is linear or small enough that simpler tools like scipy suffice
- you require a permissively licensed library without checking its custom license terms

## Facets
- artifact type: library
- maturity: active
- function: simulation, math, machine-learning, embedded
- domain: robotics, autonomous-vehicles, simulation, embedded-systems, machine-learning
- platform: windows, python, cpp, c, embedded, cross-platform
- tags: optimal-control, model-predictive-control, moving-horizon-estimation, nonlinear-programming, real-time, differentiable-optimization, casadi, simulink, matlab, octave, algorithms, linux, macos

## Member repositories
- acados/acados (main) score 93

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:45.653295+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:35:54.447080+00:00, confidence not recorded.
  - readme: https://github.com/acados/acados (fetched 2026-08-28T04:04:45.653295+00:00, sha a573f4ac3cae)
  - homepage: https://docs.acados.org (fetched 2026-08-29T11:45:28.645646+00:00, sha 8a6f7990099c)
  - site_page: https://docs.acados.org/features/index.html (fetched 2026-08-29T11:45:28.651285+00:00, sha 81a4e3b93433)
  - site_page: https://docs.acados.org/citing/index.html (fetched 2026-08-29T11:45:28.653170+00:00, sha 261e8112b5ad)
  - site_page: https://docs.acados.org/python_interface/index.html (fetched 2026-08-29T11:45:28.655561+00:00, sha e0d19894e623)
  - site_page: https://docs.acados.org/matlab_octave_interface/index.html (fetched 2026-08-29T11:45:28.658952+00:00, sha 35390d6b9f99)
  - site_page: https://docs.acados.org/installation/index.html (fetched 2026-08-29T11:45:28.649002+00:00, sha aab6a8c25099)
- Data as of 2026-08-30T08:39:29.467469+00:00.