acados/acados
Some data may be outdated — see provenance labels.
Fast and embedded solvers for nonlinear optimal control and nonlinear model predictive control observed · 2026-10-06
Health v2 · maintenance only
91/100
- Activity 98
- Release rhythm 77
- Longevity 100
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.
- gap_med: 34
- age_days: 3850
- days_rel: 75
- days_push: 15
- n_releases_24m: 12
Adoption not part of the score
1493 stars · 368 forks observed · 2026-10-06
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
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
library · maturity active
simulation math machine-learning embedded robotics autonomous-vehicles simulation embedded-systems machine-learning windows python cpp c embedded cross-platform optimal-control model-predictive-control moving-horizon-estimation nonlinear-programming real-time differentiable-optimization casadi simulink matlab octave algorithms linux macos
7 sources
- readme: https://github.com/acados/acados · fetched 2026-10-06 · a573f4ac3cae
- homepage: https://docs.acados.org · fetched 2026-08-29 · 8a6f7990099c
- site_page: https://docs.acados.org/features/index.html · fetched 2026-08-29 · 81a4e3b93433
- site_page: https://docs.acados.org/citing/index.html · fetched 2026-08-29 · 261e8112b5ad
- site_page: https://docs.acados.org/python_interface/index.html · fetched 2026-08-29 · e0d19894e623
- site_page: https://docs.acados.org/matlab_octave_interface/index.html · fetched 2026-08-29 · 35390d6b9f99
- site_page: https://docs.acados.org/installation/index.html · fetched 2026-08-29 · aab6a8c25099
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| acados/acados | main | 91 |
For agents
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