Artificial Pancreas Using Fuzzy Logic Controller

Design and optimization of a fuzzy system to control an artificial pancreas.

Artificial Pancreas Using Fuzzy Logic Controller

This example shows how to design and optimize a fuzzy inference system (FIS) tree to control an artificial pancreas. The artificial pancreas regulates the blood glucose level of an individual with type 1 diabetes using subcutaneous infusion of insulin. Type 1 diabetes is a widespread health problem that occurs when the pancreas fails to produce enough insulin to regulate blood glucose levels. To regulate the blood glucose levels, the fuzzy system uses a FIS tree, which is a distributed, connected representation of multiple FISs, each with a small rule base. A FIS tree provides easier understanding of the inference process and allows faster performance optimization with a small number of tunable parameters.

Setup

1. Clone project repository: git clone https://github.com/mathworks/Artificial-Pancreas-Using-Fuzzy-Logic-Controller.git
2. Run example: Open and run artificialPancreasWithFISTreeControl.slx in Simulink®

MathWorks Products (https://www.mathworks.com/)

Requires MATLAB release R2022 or newer

• Fuzzy Logic Toolbox™
• Global Optimization Toolbox™
• Simulink®

Getting Started

• Design Controller for Artificial Pancreas Using Fuzzy Logic
• Video: Artificial Pancreas Control Using Fuzzy Logic

License

The license is available in the License file within this repository.

Community Support

Copyright 2022-2023 The MathWorks, Inc.