Abstract
We present an automatic code generation tool, AutoGenU for Jupyter, for nonlinear model predictive control (NMPC) with a user-friendly and interactive interface utilizing JupyterLab and Jupyter Notebook. We utilize a symbolic computation package SymPy for automatic C++ code generation. We also developed numerical solvers of NMPC using the continuation/GMRES (C/GMRES) method and multiple-shooting-based C/GMRES method in C++. AutoGenU for Jupyter provides the simulation environment of NMPC with these solvers and visualization of the simulation results. We give an example of code generation and numerical simulation of a swing-up control of a cart pole using AutoGenU for Jupyter.
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