NNFL LAB
About LAB
A Neural Network and Fuzzy Logic Lab is designed to provide hands-on experience in artificial intelligence (AI), machine learning (ML), and computational intelligence techniques. This lab enables students to explore the integration of neural networks and fuzzy logic, which are widely used in decision-making, pattern recognition, control systems, and various engineering applications.
Objectives of the Lab
• To understand the fundamental principles of neural networks and fuzzy logic.
• To implement different types of artificial neural networks (ANN) and train them for various applications.
• To design and analyze Fuzzy Logic Controllers (FLC) for decision-making under uncertainty.
• To develop Hybrid Neuro-Fuzzy Systems that integrate the learning capability of neural networks with the reasoning power of fuzzy logic.
• To use MATLAB, Python, or other software tools for simulation and implementation.
• To apply neural networks and fuzzy logic in real-world applications such as robotics, control systems, image processing, and pattern recognition.
Key Components of the Lab
1. Software Tools Used
- MATLAB with Neural Network & Fuzzy Logic Toolbox
- Python (TensorFlow, Keras, PyTorch, Scikit-Fuzzy, SciPy)
- Simulink for system modeling and simulation
- R and OpenAI Gym for reinforcement learning applications
2. Hardware (if used for real-time applications)
- Microcontrollers (Arduino, Raspberry Pi, ESP32) for fuzzy and neural-based control systems
- Digital Signal Processing (DSP) boards for ANN-based computations
- Sensors for real-time data acquisition in control applications
List of Experiments:
|
Sr. No. |
Title of Lab Experiments | CO |
| 1. | Write a program in MATLAB to plot triangular, trapezoidal, and bell-shaped membership functions | CO3 |
| 2. | Write MATLAB program for Back Propagation Neural Network Algorithm. | CO2 |
| 3. | To write a Program in MATLAB to perform addition, subtraction, and multiplication operations of fuzzy set. | CO3 |
| 4. | Simulate a Fuzzy logic-based boost converter | CO3 |
| 5. | Write a program in MATLAB to implement AND gate using artificial neural network with Back Propagation
algorithm |
CO2 |
| 6. | To design a neural network using neural network toolbox to identify the
given data set. |
CO2 |
| 7. | To design a controller using FIS (Fuzzy Inference Editor). | CO4 |
| 8. | Write a Matlab program to implement AND function using perceptron networks with bipolar inputs and outputs. | CO1 |
| INNOVATIVE EXPERIMENTS | ||
| 1. | Design a fuzzy controller to calculate the washing time of washing machine. | CO4 |
| 2. | Design and simulate an air conditioning system using fuzzy logic control | CO4 |
NOTE: – At least 8 Experiments out of the list must be done in the semester.