acados
blasfeo
| acados | blasfeo | |
|---|---|---|
| 5 | 6 | |
| 677 | 278 | |
| 3.0% | - | |
| 8.9 | 5.3 | |
| 7 days ago | 7 months ago | |
| C | Assembly | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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acados
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How to understand Model Predictive Control
I would check out CasADi (specifically the opti framework) and or ACADOS. To code up a quick MPC in general is not hard, but to squeeze efficiency and exploit sparsity for good real-time performance is a little more involved and these tools really help with that.
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Question about Model Predictive Control (MPC) cost function
Generally, nonlinear MPC uses either IPOPT (an interior point method) or sequential quadtraic programming based approaches (google GURBOI, qpoases, qrqp...). A good python framework is CasADi, or its sister project ACADOS. I think there is also a fair amount of literature on learning MPC cost functions from data you could probably find.
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Show HN: prometeo – a Python-to-C transpiler for high-performance computing
Thanks for the question! My background is in numerical optimization for optimal control. Projects like this https://github.com/acados/acados motivated the development of prometeo. It's mostly about solving optimization problems as fast as possible to make optimal decisions in real-time.
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Do you know a good free toolbox on mpc control for GNU Octave?
Look at Acados. I didn't use it with Octave, but according the readme it has a interface with Octave.
blasfeo
- Blasfeo - Basic linear algebra subroutines for embedded optimization
- Blasfeo – Basic linear algebra subroutines for embedded optimization
- Where can I find safety critical or hard real-time C or C++ libraries?
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Show HN: prometeo – a Python-to-C transpiler for high-performance computing
Intrinsics (or directly assembly) are used in BLASFEO (https://github.com/giaf/blasfeo) the linear package used by prometeo. It would be cool to generate assembly directly for a few things, but that would require quite a bit of work!
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Parsing Protobuf at 2+GB/s: How I Learned To Love Tail Calls in C
I'm wondering how the tailcalls would fair against the assembly code for linear algebra, like for example in the blasfeo library.
What are some alternatives?
StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)
hpipm - High-performance interior-point-method QP and QCQP solvers
pyomo - An object-oriented algebraic modeling language in Python for structured optimization problems.
OpenBLAS - OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version.
py2many - Transpiler of Python to many other languages
Octavian.jl - Multi-threaded BLAS-like library that provides pure Julia matrix multiplication
blas - Wrappers for BLAS (Fortran)
Metatheory.jl - General purpose algebraic metaprogramming and symbolic computation library for the Julia programming language: E-Graphs & equality saturation, term rewriting and more.
MatrixEquations.jl - Solution of Lyapunov, Sylvester and Riccati matrix equations using Julia
blis - BLAS-like Library Instantiation Software Framework