A fuzzy logic controller designed to regulate fuel flow based on vehicle speed, load, and engine RPM. Developed as part of the AI Techniques (MOD006564) module at Anglia Ruskin University, this project demonstrates the power of fuzzy inference systems (FIS) for real-time decision-making.
- Supporting Documents: Project brief, assignment instructions, and other materials provided by the university.
- Visual Outputs: Membership function graphs and 3D surface plots illustrating system behaviour.
- MATLAB Implementation: Core logic for the fuzzy fuel controller (includes
.mscript and fuzzy inference system files). - Important Note: The MATLAB code, FIS files, and the final report have been excluded from this repository to maintain academic integrity and comply with university guidelines.
This project uses fuzzy logic to control fuel flow based on three key vehicle parameters:
- Speed (1–120 mph)
- Load (100–1000 kg)
- RPM (1000–6000)
The fuzzy logic controller uses membership functions to interpret the inputs and calculates a continuous fuel output between 0.5–3.5 L/h. The system provides smooth and adaptive fuel flow adjustment without abrupt transitions, making it ideal for real-time automotive applications.
Below are the MATLAB-generated membership functions and 3D surface plots used to validate the system’s performance.
This graph visualises the fuzzy membership functions for speed: Slow, Medium, Fast, and Very Fast.
The load membership function graph displays fuzzy categories for vehicle load: Light, Medium, Heavy, and Very Heavy.
This graph shows how RPM is categorised into Green, Yellow, Orange, and Red zones, indicating increasing engine strain.
This graph illustrates the fuzzy membership functions for fuel output, ranging from Very Low to Very High.
These surface plots illustrate the relationship between inputs (speed, load, RPM) and fuel output. The plots show how fuel flow logically increases as speed, load, and RPM rise.
This 3D surface plot shows how the controller adjusts fuel flow as vehicle speed and RPM change.
This plot demonstrates how higher load and RPM increase fuel output, confirming the system’s correct behaviour.
The system uses fuzzy sets to categorise the inputs (speed, load, RPM). The fuzzy sets allow smooth transitions between states, ensuring human-like reasoning for fuel flow adjustments.
The controller’s rule base consists of simple if-then rules to produce the fuel output. The rules are based on logical combinations of input variables, such as "IF Speed IS Fast AND Load IS Heavy THEN Fuel IS High".
Surface plots provide a visual representation of how input variables interact with the fuel output. The system’s output is continuous and smooth, as shown by the surface plots, confirming its capability to handle real-time adjustments.
To replicate or test the fuzzy logic system, you will need:
- MATLAB with the Fuzzy Logic Toolbox installed.
- Clone the repository:
git clone https://github.com/QuantumAlchemist03/fuzzy-fuel-injection-controller.git # 🚫 **Academic Integrity**
The MATLAB code and FIS files are excluded from this repository to adhere to academic integrity and university guidelines.
Additionally, final reports and assignment-sensitive files have been omitted to ensure full compliance with university submission protocols.
This project demonstrates the use of fuzzy logic in real-time systems. By applying fuzzy inference systems (FIS), the controller adapts dynamically to inputs such as speed, load, and RPM. The system ensures smooth fuel flow adjustment based on human-understandable fuzzy sets, replacing traditional logic-based control systems with more adaptable and human-like reasoning.
Feel free to explore the visual outputs of the fuzzy system and how it reacts to different conditions in real-time.
This repository is for academic reference and educational purposes only.
All the files, code, and documents in this repository are not for commercial use and are provided under the following terms:
- Non-Commercial Use: You may use, copy, modify, or distribute this code and its components for educational and academic purposes only.
- Academic Use Only: You may use this project and its materials for your own academic work or for reference but may not use it for any commercial purposes.
- No Warranty: The code and materials are provided "as is," with no warranty or guarantee of any kind, either expressed or implied.
Disclaimer: This license is specifically designed for educational and academic purposes. If you wish to use this work outside of the scope of educational activities (e.g., for commercial or professional projects), you must seek permission from the original author (Alif Sathar) and abide by the licensing terms agreed upon.