Quadcopter-control-and-trajectory-visualization

Contents:

• Modelization, simulation and control of a quadcopter UAV
• Visualization of its trajectory and tracking performance
• Implementation of different nonlinear controlers (upcoming)
• Development of state estimators based on noisy measurements and inputs, and performance assessment (upcoming)
• Control based on the state estimates (to do)
• Add perturbations (wind gust) and parametric uncertainties (to do)
• Assess controlers robustness (to do)

The quadrotor is modeled using the full 6-DOF Newton–Euler equations (second law of Newton and Euler’s rotation equations), including nonlinear couplings, gyroscopic moments, and cross-inertia effects. A reference trajectory is used to evaluate controller precision and robustness (to do).

Quadrotor System Overview

State vector

$X = [x,y,z,\dot{x},\dot{y},\dot{z},\phi,\theta,\psi,\dot{\phi},\dot{\theta},\dot{\psi}],$

where:

• $(x, y, z)$: position
• $\dot{x},\dot{y},\dot{z}$: translational velocity
• $(\phi, \theta, \psi)$: roll, pitch, yaw
• $\dot{\phi},\dot{\theta},\dot{\psi}$: angular velocity

Control input

• Rotation speed control for each motor (quadcopter: 4 motors)

$u_\omega =[\omega_1,\omega_2,\omega_3,\omega_4]$

To simplify we can consider command in torque that will be converted into a command in rotation speed of each motor:

$u = [u_1,u_2,u_3,u_4]^\top = [T_B,\tau_{\phi},\tau_{\theta},\tau_{\psi}]^\top,$

where:

• $T_B$: total thrust
• $(\tau_{\phi},\tau_{\theta},\tau_{\psi})$: roll, pitch, yaw torques

Control loop scheme

Goal:

Follow the reference trajectory * 🔵 with the best possible accuracy.

➡️🚩✅

How to use it

1. Add the entire folder to the MATLAB path: addpath(genpath("path/folder"))
2. Run the main script quadcopter_command_main.m using MATLAB to launch the simulation
3. Run the script plot3D_anime_body_frame.m to launch the animation window displaying the 3D trajectory of the quadcopter, its state evolution and the position reference to follow

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