IMPACT: A Toolchain to Simulate and Deploy Nonlinear Model Predictive Control. Documentation example

This code executes the example provided in the Impact toolchain documentation, implemented in Python but also available in Matlab. It first defines the system model, followed by the formulation of the optimal control problem OCP. A transcription method and a solver are then selected, in this case, the Fatrop solver. The problem is solved, and the results are plotted. Next, the same process is executed in a loop to emulate Model Predictive Control MPC, and the corresponding results are also visualized. Finally, the problem is exported and the associated artifacts are generated, including C functions, a Simulink block, and a ROS 2 node.