Author: Davide Carecci
Initial commit: 02.09.2025
⚠️ This repo uses Git LFS - do not download as ZIP (see Notes section of this README). ⚠️ The general_utils library contains also a user manual to setup VSCode/Python for non-expert users and the list of the required standard Python libraries (download it from the GitHub repository).

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BIOGoAlS.Select is a feedback control tool designed for experimental validation of predictive and override control strategies to enhance biomethane production efficiency and process safety.

The tool has undergone two major experimental validation campaigns:

• First campaign (10.2023–04.2024):
  Conducted at Laboratory A. Rozzi (Politecnico di Milano, Cremona campus) on the UIT machine.

• Second campaign (03.2025–07.2025):
  Conducted at BioTA Lab (Universidad Técnica Federico Santa María, Valparaíso, Chile) using a hand-made, Raspberry-Pi-driven control architecture.

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Documentation

• UIT Software User Manual
  Additional information on integration between this program and the UIT proprietary software.

• SelectorPI Pseudo-Code
  Step-by-step guidance through the code, both from mathematical and conceptual (simplified) standpoints.

• BIOGOALS.SELECT User Manual
  Comprehensive documentation of the repository structure and main scripts:

  • /UIT_implementation/UIT_selectorPI_operative.py
  • /RPi_implementation/RPi_selectorPI_operative.py

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Inside the /UIT_implementation folder:

• Python code to run the BIOGoAlS.Select tool — a 'conventional' online feedback PI controller with an override structure to improve biomethane production under safety constraints. Executable only on the UIT machine.

• Jupyter Notebook for reading, analyzing, and plotting controller outputs.

• CSV input file for setpoint data. For the notebook to run, data generated by the UIT proprietary software must be manually added.

• Examples of figures, output CSV files, and configuration INI files.

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Inside the /RPi_implementation folder:

• Python code to run the BIOGoAlS.Select tool — improved and adapted for the hand-made, Raspberry-Pi-driven control architecture used in Chile’s experiments. Ready to run when called from the terminal or a Jupyter Notebook.

• Jupyter Notebook for running a closed-loop test (together with a Python code to call the simulator of a real plant from the BIOGoAlS.agri-AcoDM tool) $\leftrightarrow$ sub-folder with an example of inputs and outputs required and generated.

• /Input subfolder: contains required CSV input data for the Python code.

• Examples of plots, logs and output files.

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Notes

• Markdown links (./folder/file) are used for proper GitHub rendering.

• Avoid editing files inside /UIT_implementation unless you have access to the UIT system.

• Python 3.10+ is required for the RPi implementation.

• Python 3.8- is required for the UIT implementation.

• A Jupyter Notebook to find the best design of the controller (optimization) is also present.

• For further details, please refer also to the PhD thesis of the author (visit POLItesi or request a copy to davide.carecci@polimi.it).

• ⚠️ Important: Git LFS Required This repository uses Git LFS (Large File Storage). ❌ Do NOT download the project using "Download ZIP" — files will be incomplete. ✅ Instead, clone the repository:

  git clone <repo-url> cd <repo> git lfs pull

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© 2025 Davide Carecci — All rights reserved.**