Quadcopter Control Simulation

Project Overview

This project involves modeling, simulating, and controlling a quadcopter drone under various scenarios using MATLAB. The project demonstrates the quadcopter's behavior through both non-linear and linearized dynamic models.

Getting Started

To use this project, ensure MATLAB is installed on your system. You can clone or download this repository to begin.

Directory Structure

• Q1: Non-linear model simulations.
• Q2: Comparison between non-linear and linearized models.
• Q3: Implementation of a full-state feedback controller.
• Q4: Incorporates sensor noise and environmental disturbances into the simulation.

Running Simulations

Each question's folder contains a specific MATLAB script Sim_Quadcopter.m for running simulations relevant to that question.

Simulation Scenarios

• Free Fall: Simulates the quadcopter in a free fall with engines off.
• Equilibrium: Maintains a steady altitude and orientation.
• Rotation at Constant Altitude: Demonstrates spinning at a fixed altitude by adjusting the torque.
• Linear vs Non-linear Model: Examines behaviors under conditions that either favor or challenge the linear model.
• Controlled Trajectory Flight: Uses a state feedback controller to follow a designated path.
• Disturbed Flight: Simulates flight under realistic sensor noise and environmental disturbances.

How to Run

1. Basic Simulations (Q1 & Q2):

   • Navigate to the respective folder for the question.
   • Open and run Sim_Quadcopter.m in MATLAB.
   • Modify parameters within the script to see different behaviors.

2. Advanced Control Simulations (Q3 & Q4):

   • Similar to the basic simulations, open and run the Sim_Quadcopter.m script in the respective directory.
   • These scripts integrate more complex features like controllers and observers into the simulations.

Results Analysis

Plots and results are automatically saved in the plots folder for each question. Detailed observations can be made by examining these outputs.

License

This project is licensed under the MIT License - see the LICENSE file for more details.

Acknowledgments

• Special thanks to Andrew Gibiansky for foundational resources on quadcopter dynamics.
• Gratitude to course staff and teaching assistants for their invaluable support.