ControlSystems.jl
harold
| ControlSystems.jl | harold | |
|---|---|---|
| 2 | 2 | |
| 489 | 171 | |
| 1.4% | - | |
| 8.6 | 1.8 | |
| about 1 month ago | 10 months ago | |
| Julia | Python | |
| GNU General Public License v3.0 or later | MIT License |
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ControlSystems.jl
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What is the status of libraries in julia for control systems analysis and design?
control system toolbox -> ControlSystems.jl
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Control theory related open source project
Find an open-source controls library on GitHub (this one's my favorite) and search the Issues tab for something that everyone agrees would be nice to have/fix but no one has gotten around to implementing/fixing. If it's something you feel comfortable implementing, ask the maintainers if they wouldn't mind if you submitted a pull request for the new feature/bugfix.
harold
- harold open source controls package for Python - v1.0.2 announcement
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Control theory related open source project
I have a project here https://github.com/ilayn/harold that I have been neglecting for quite a while now.
What are some alternatives?
ComponentArrays.jl - Arrays with arbitrarily nested named components.
Dask - Parallel computing with task scheduling
DSGE.jl - Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)
PyMC - Bayesian Modeling and Probabilistic Programming in Python
PowerSimulationsDynamics.jl - Julia package to run Dynamic Power System simulations. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
MatrixEquations.jl - Solution of Lyapunov, Sylvester and Riccati matrix equations using Julia
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
KiteSimulators.jl - Simulators for kite power systems
RDKit - The official sources for the RDKit library
DiscretePIDs.jl - Discrete-time PID controllers in Julia
NumPy - The fundamental package for scientific computing with Python.