Applied Flight Performance & Control: Theory to Simulation

"A complete, physics-based flight simulation framework bridging the gap between theoretical aerodynamics and practical mission analysis."

✈️ Project Overview

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.

📚 Course Modules & Repository Structure

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`

🚀 Getting Started

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_Analysis and 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).

📊 Sample Output: Mission Dashboard

The simulation automatically generates telemetry for trajectory, energy states, and control inputs.

(Note: Visuals are generated directly from the course capstone project.)

🛠️ Tech Stack

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

👨‍💻 Author & Instructor

Kıvanç Apaydın Aeronautical Engineer | Flight Physics

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