MDPs and POMDPs in Julia - An interface for defining, solving, and simulating fully and partially observable Markov decision processes on discrete and continuous spaces.
-
Updated
Jul 22, 2024 - Julia
MDPs and POMDPs in Julia - An interface for defining, solving, and simulating fully and partially observable Markov decision processes on discrete and continuous spaces.
An open source model predictive control package for Julia.
System Identification toolbox, compatible with ControlSystems.jl
Computing reachable states of dynamical systems in Julia
Arrays with arbitrarily nested named components.
A Control Systems Toolbox for Julia
Robust and optimal design and analysis of linear control systems
Solution of Lyapunov, Sylvester and Riccati matrix equations using Julia
Manipulation of generalized state-space (descriptor) system representations using Julia
Particle Gibbs-based optimal control with performance guarantees for unknown systems with latent states
AirBorne a complete algorithmic trading framework in Julia.
Like reinforcement learning, but it works in practice
State estimation, smoothing and parameter estimation using Kalman and particle filters.
Interface between ControlSystems and ModelingToolkit
Discrete-time PID controllers in Julia
Create reduced-order state-space models for lithium-ion batteries utilising realisation algorithms.
An unofficial implementation of publicly available approximated polynomial models for NASA's Generic Transport Model aircraft.
Passivity-preserving model reduction for descriptor systems via spectral factorization
A powerful, no code solution for control and systems engineering
Add a description, image, and links to the control-systems topic page so that developers can more easily learn about it.
To associate your repository with the control-systems topic, visit your repo's landing page and select "manage topics."