Fast and embedded solvers for nonlinear optimal control and nonlinear model predictive control
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Updated
Jan 7, 2026 - C
Fast and embedded solvers for nonlinear optimal control and nonlinear model predictive control
HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems
An optimization framework that links CasADi, Ipopt, ACADOS and biorbd for Optimal Control Problem
An open source model predictive control package for Julia.
Implementation of Kalman Filter, Extended Kalman Filter and Moving Horizon Estimation to the stirred tank mixing process.
Nonlinear Model Predictive Control (NMPC) based on CVXPY and JAX in Python
path-planning|control|sensor-fusion algorithmic components for mobile robotics
Source code of paper "Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling".
Rotor's dynamics calibration tests combining XBot2 rt plugins and a simple approach to linear MHE.
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