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How to use fuzzy logic toolbox in Matlab

How to use fuzzy logic toolbox in Matlab


In this Blog, we'll explore how to use the Fuzzy Logic Toolbox in MATLAB to solve a tipping problem. Imagine you're at a restaurant and need to decide the tip based on service and quality. Let's dive into the process.

Setting Up the Fuzzy Logic System

Define Input Variables:

  • We consider two factors: Service and Quality.

  • Membership functions for Service: Low, Medium, High.

  • Membership functions for Quality: Low, Medium, High.

Define Output Variable:

  • We categorize Tip into three levels: Low, Medium, High.

Creating Fuzzy Rules:

  • Establish rules connecting inputs to output (e.g., If Service is Low and Quality is High, then Tip is Medium).

  • Rules cover various combinations of service and quality.

Rule Viewer:

  • Visualize and review the rules created for the fuzzy logic system.

Exporting Fuzzy Logic System

Export the fuzzy logic system to a file . This file will be useful for future use and integration into other models.

Integrating Fuzzy Logic into MATLAB Model

Using Fuzzy Logic Controller:

  • Import the fuzzy logic system into MATLAB.

  • Create input signals for Service and Quality.

  • Display the Tip output.

Simulating Results:

  • Simulate the model and observe the Tip output based on different combinations of Service and Quality values.

Observing Results

  • Adjust Service and Quality values to see how the Tip output changes.

  • The fuzzy logic system uses the defined rules to determine the appropriate tip based on the inputs.


This example demonstrates the usage of the Fuzzy Logic Toolbox in MATLAB to model a tipping problem. You can adapt this approach for other applications by defining relevant input and output variables, creating membership functions, and establishing rules.

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