Usage

Usage#

Example Scripts#

The example scripts lti_dd_mpc_example.py and nonlinear_dd_mpc_example.py demonstrate the setup, simulation, and data visualization of the Data-Driven MPC controllers applied to Linear Time-Invariant (LTI) and nonlinear systems, respectively.

To run the example scripts, use the following commands:

Data-Driven MPC for LTI systems#

Run the example script with a seed of 18, a simulation length of 400 steps, a verbosity level of 1, and save the generated animation to a file:

python examples/lti_control/lti_dd_mpc_example.py --seed 18 --t_sim 400 --verbose 1 --save_anim

Data-Driven MPC for Nonlinear systems#

Run the example script with a seed of 0, a simulation length of 3000 steps, a verbosity level of 1, and save the generated animation to a file:

python examples/nonlinear_control/nonlinear_dd_mpc_example.py --seed 0 --t_sim 3000 --verbose 1 --save_anim

Note

The --save_anim flag requires FFmpeg to be installed. See the Requirements section for more details.

Customizing Controller Parameters#

To use different controller parameters, modify the configuration files in examples/config/controllers/ for each controller, or specify a custom configuration file using the --controller_config_path argument.

Customizing System Models#

Example system parameters are defined in examples/config/models/.

LTI system: Parameters can be modified directly in four_tank_system_params.yaml.
Nonlinear system: The system dynamics are defined in nonlinear_cstr_model.py and its parameters in nonlinear_cstr_system_params.yaml.

Customizing Plots#

Matplotlib properties for input-output plots can be customized by modifying plot_params.yaml.

Additional Information#

Some key arguments used in the scripts are listed below:

Argument	Type	Description
`--controller_config_path`	str	Path to the YAML file containing Data-Driven MPC controller parameters.
`--t_sim`	int	Simulation length in time steps.
`--save_anim`	flag	If passed, saves the generated animation to a file using FFmpeg.
`--anim_path`	str	Path where the generated animation file will be saved. Includes the file name and its extension (e.g., `data-driven_mpc_sim.gif`).
`--verbose`	int	Verbosity level: `0` = no output, `1` = minimal output, `2` = detailed output.

To get the full list of arguments, run each script with the --help flag.

For a deeper understanding of the project and how the controllers operate, we recommend reading through the scripts and the docstrings of the implemented utility functions and classes. The documentation includes detailed descriptions of how the implementations follow the Data-Driven MPC controller schemes and algorithms described in the referenced papers.