Model, Identification and Optimal Control of a Multispectral Optogenetic Simulator

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Repository Structure

The repository is organized into two main folders:

notebooks/

• bounds_simulation.ipynb: Grid search algorithm to find the operational bounds.
• main_simulation.ipynb: Simulates the DIYA system for multiple inputs (ambient temperature, LED light, controller, ...)
• symbolic_ODE_ss_matrices.ipynb: Symbolic equations from the modeling.
• test_communicator.ipynb: NOT FINISHED: used to run real experiments.

src/

Contains folders used to run the simulations and real experiments, as well as images or outputs from the simulations:

classes/

• diya_communicator.py: NOT FINISHED: used to connect with the DIYA device for real experiments.
• LED_params.py: Connects the Program from biologists with power consumption and waste heat.
• model.py: Model of the components.
• mqtt_listener.py: File written by Samuel Balula to plot live operations.
• simulation.py: Simulation class that runs the model given a controller and parameters from the LED.

controllers/

• controller_base.py: Base abstract class for the controllers.
• PID, LQR, MPC, ...

data/

• battery/: Matlab codes to analyze and estimate the battery parameters.
• fan/: To analyze and estimate the fan parameters.
• fan/: To analyze and estimate the Peltier module parameters.

helper_functions/

• phase_portraits/: Matlab folder downloaded online for plotting.
• rga/: Matlab folder downloaded online for Relative Gain Array calculation.

img/

Contains .pdf plots for the report.

• __init__.py: Contains the function that saves the pdf.

measurements/

Contains .csv file from real experiments (THE PATH NOW IN diya_communicator.py IS NOT UPDATED AND SHOULD BE IMPLEMENTED IN __init__.py)

output_notebooks/

Contains .pdf plots for the report.

• __init__.py: Contains the functions that save the bounds and ss-matrices.
• operational_bounds/: Contains .csv files with values of the parameters of the least-squares of the bounds.
• state_space/: Contains .csv files with the state-space matrices.

Prerequisites

The project requires Python 3.11 or higher. To set up the project, run the following commands:

macOS/Linux

git clone git@github.comJackmastro/Semester_Project.git
cd Semester_Project
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
pip install -e .

Windows

git clone git@github.com:Jackmastro/Semester_Project.git
cd Semester_Project
python -m venv venv
.\venv\Scripts\activate
pip install -r requirements.txt
pip install -e .

Work in Matlab

Always run setup.m to add all path to the working directory. Navigate to the src/data folder to find the Matlab scripts used for plotting and fit the data.

Running Simulations in Python

To run the experiments, navigate to the notebooks/ folder and execute the desired Jupyter notebook.

Authors

Giacomo Matroddi