ohtsukalab/autogenu-jupyter
An automatic code generator for nonlinear model predictive control (NMPC) and the continuation/GMRES method (C/GMRES) based numerical solvers for NMPC
This project helps control engineers and robotics researchers quickly implement and test advanced nonlinear model predictive control (NMPC) strategies. You provide the mathematical description of your system's dynamics, constraints, and cost function, and it automatically generates optimized C++ and Python code for real-time control. The output is deployable control code and simulation results, enabling rapid prototyping for complex systems like drones or robotic arms.
178 stars. No commits in the last 6 months.
Use this if you need to design and implement high-performance, real-time nonlinear model predictive control for your robotic or dynamic system.
Not ideal if you are looking for a pre-built, off-the-shelf controller for a simple linear system or don't have experience defining optimal control problems.
Stars
178
Forks
38
Language
C++
License
MIT
Category
Last pushed
Jul 01, 2025
Commits (30d)
0
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