Quadcopter UAV Control Simulation

This repository contains a complete MATLAB/Simulink project for simulating the flight dynamics and control of a 6-DOF Quadcopter Unmanned Aerial Vehicle (UAV). The project implements a cascade control strategy to track complex 3D trajectories (such as a spiral ascent).

📝 Overview

The simulation models the physics of a quadrotor, including rigid body dynamics, motor mixing, and environmental feedback. It utilizes a feedback control loop to adjust the rotor speeds ($w_1$ to $w_4$) based on the error between the desired trajectory and the current state.

Key Features

• Full Dynamics Model: Includes specific blocks for Attitude and Position integration.
• Cascade Control: Separated loops for position tracking and attitude stabilization.
• 3D Visualization: A post-processing script animates the drone's orientation and path.
• Data Logging: Real-time plotting of Euler angles and XYZ coordinates.

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🏗️ System Architecture & Simulink Models

The system is built in Simulink (demo.slx). Below are the details of the internal subsystems.

1. Top-Level Simulation Model

This is the main simulation loop. It connects the Control Algorithm, the Quadcopter Plant (Dynamics), and the Reference Trajectory generation.

2. Control Algorithm

The controller takes the reference position ($x_d, y_d, z_d$) and current state, processes them through PID loops, and outputs the required motor mixing signals ($U_1, U_2, U_3, U_4$).

3. Attitude Calculation Module

This subsystem calculates the Euler angles ($\phi, \theta, \psi$) by integrating the angular rates, converting the body-frame angular velocities to the inertial frame.

4. Position Calculation Module

This block is responsible for integrating the linear accelerations and velocities to determine the drone's absolute position ($x, y, z$) in 3D space.

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📊 Simulation Results

After running the simulation, the run.m script generates the following visualizations to validate performance.

1. 3D Trajectory Visualization

The drone (represented by the red/blue cross) successfully tracks a spiral climbing path. The green dot indicates the reference target.

2. Position Tracking Performance

Comparison between Reference Position (Red Dashed) and Actual Position (Blue Solid).

• X/Y: Shows smooth sinusoidal tracking.
• Z: Shows a linear altitude increase.

3. Attitude (Euler Angles) Response

The plots below show the Roll ($\phi$), Pitch ($\theta$), and Yaw ($\psi$) angles generated by the controller to execute the spiral maneuver.

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🚀 How to Run

1. Clone the Repository:

   git clone https://github.com/swzhangf/Quadcopter-UAV-Control-Simulation.git

2. Open MATLAB: Ensure you have MATLAB and Simulink installed.
3. Run Simulation:
   • Open demo.slx.
   • Click the Run button in Simulink.
   • Wait for the simulation to finish (workspace variables like tout, x, y will be created).
4. Visualize:
   • Open run.m.
   • Run the script to see the 3D animation and generate the plots.

📂 File List

• demo.slx: Main Simulink model file.
• run.m: Visualization and plotting script.
• drone.m: Helper function for calculating the rotation matrix ($C_{bn}$) for 3D plotting.
• *.jpg: Project documentation images.

📜 License

This project is open-source and available under the MIT License.