"A complete, physics-based flight simulation framework bridging the gap between theoretical aerodynamics and practical mission analysis."
This repository acts as the official companion codebase for the Udemy course.
Start building your own flight simulator today:
This repository houses the source code, datasets, and simulation scripts for the "Applied Flight Performance & Control" engineering course.
Using the Northrop T-38 Talon as a primary case study, this project demonstrates how to build a high-fidelity 3-DOF Flight Simulator from scratch. Unlike standard textbook examples, this framework integrates real-world complexities:
- Non-Linear Aerodynamics: Calibrated CFD data (OpenVSP) validated against wind tunnel experiments.
- Dynamic Propulsion: J85-GE-5 turbojet performance maps varying with Altitude and Mach (Generated via GasTurb).
- Adaptive Autopilot: A gain-scheduled flight control system that handles 11 distinct mission phases.
This project is modular by design. Each folder corresponds to a specific learning module in the course curriculum:
| Module | Description | Key Tech |
|---|---|---|
Flight_Physics_Engine |
Core Solver. Calculates Forces, Moments, and State Derivatives (Equations of Motion). | MATLAB, ODE Solvers |
Automatic_Control |
Autopilot Design. Optimization scripts for tuning PID gains across different flight regimes (Rotation, Flare, etc.). | fminsearch, PID Control |
Full_Mission_Profile_Analysis |
Executive Script. Integrates engine and autopilot to fly a complete "Gate-to-Gate" sortie. | System Integration |
Calibrate_OpenVSP_Data |
Data Science. System ID tools to correct inviscid VSP data using experimental wind tunnel results. | Curve Fitting |
J-85-GE_Thrust_Data |
Propulsion. Digitized performance maps for the T-38's Turbojet engines. | GasTurb, Interpolation |
Data_Handling |
Utilities. Scripts for processing drag polars, atmospheric models, and unit conversions. | Data Processing |
To run the full mission simulation on your local machine:
-
Clone the Repository:
git clone [https://github.com/KivancApaydin1907/Applied_Flight_Performance_Udemy_Course.git](https://github.com/KivancApaydin1907/Applied_Flight_Performance_Udemy_Course.git)
-
Setup MATLAB Path: Open MATLAB and ensure all subfolders are added to your path (Right Click Folder -> Add to Path -> Selected Folders and Subfolders).
-
Run the Simulation: Navigate to
Full_Mission_Profile_Analysisand execute:Full_Mission_Simulation -
Analyze Results: The script will output a mission summary to the command window and generate dashboard plots (Trajectory, Energy States, Control Inputs).
The simulation automatically generates telemetry for trajectory, energy states, and control inputs.
(Note: Visuals are generated directly from the course capstone project.)
- Language: MATLAB R2025b (Backward compatible to R2020a)
- Aerodynamics: OpenVSP (Vortex Lattice Method)
- Propulsion: GasTurb (For engine cycle data generation)
- Optimization: Nelder-Mead Simplex Method (
fminsearch) - Control Theory: Classical PID, Cascade Control, Gain Scheduling
Kıvanç Apaydın Aeronautical Engineer | Flight Physics
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