
Model and simulate a DJI mavic pro-style drone in MATLAB and Simulink, derive symbolic dynamics, analyze thrust, drag, gravity and gusts, and design a pid controller for position and attitude.
Analyze the battery specifications and performance of a three-cell LiPo pack, including 11.4 V nominal, 3,800 mAh per cell, 77 A max discharge, and motor limits in Simulink.
Model and simulate a brushless dc motor with kv, back-emf, and voltage-load effects; fit a cubic relation rpm ≈ -2.6931 v^3 + 1400 v to predict speed under load.
We empirically model propeller performance using blade element and momentum theories, using data to relate rpm, thrust, torque, and current for hover.
Model a drone's linear and rotational dynamics using a four-rod frame, derive translational motion via Newton's laws and rotational motion via moments of inertia about x, y, and z.
Model thrust and moments from propellers to control a drone, analyze pitch and roll by selective thrust changes, and incorporate drag and disturbances using a simple constant area model.
Explore thrust vectors and linear forces acting on a drone, detailing how roll and pitch alter propeller thrust components and how to project forces into x, y, and z axes.
Set up a Simulink project in Matlab and build the motors and propellers block to model thrust, torque, and current using Matlab functions.
Implement rotational dynamics in a MATLAB function block, compute angular acceleration from moments and inertia on the x, y, z axes, then integrate to angular velocity and angle.
Compute drone accelerations in x, y, z from thrust from propellers, drag, disturbances, gravity, and then integrate to obtain velocity and position.
Create a MATLAB disturbance function that converts wind gusts into drag disturbances, inputting them into the linear dynamics block to model aerodynamic forces on the drone.
Learn how to convert throttle and attitude inputs into motor voltage signals for a four-motor drone in an open-loop MATLAB and Simulink model, with symmetric control and future automation.
Test and debug the open loop drone model in Simulink by feeding throttle commands, visualizing attitude, position, and acceleration with scopes and displays, and exploring wind disturbances to understand dynamics.
Visualize the drone’s 3D trajectory by exporting simulation data from SIMULINK to the MATLAB workspace and plotting the x, y, z coordinates in a 3D plot.
Explore automated altitude control for a drone using a PID controller in a closed-loop Simulink model, including throttle regulation, wind considerations, and gain tuning.
Implement a quadcopter PID control system in MATLAB and Simulink, focusing on rotational rate control for pitch and roll with throttle as the power input.
One of the only comprehensive, detailed and approachable online courses taking you from the mathematical modelling of a quadcopter drone to MATLAB/SIMULINK implementation and PID control design.
Today, drones are everywhere, from ultra high tech military devices to toys for kids going through advanced flying cameras and much more. How do such "apparently" simple machines achieve such precise and impressive flights in varying unstable and unpredictable environmental conditions.
This course gives you the opportunity to learn and do the following:
- Understand and harness the Physics behind a Quadcopter Drone.
- Establish and approximate the Physics of DC motors and propellers from experimental data.
- Derive the mathematical equations behind the rotational and linear dynamics of a drone.
- Implement them in engineering model in MATLAB & SIMULINK using blocks, MATLAB functions, etc.
- Test and fit your model to relevant real life performance and inputs.
- Implement, test and tune PID controllers adapted to your requirements in order to control the output of your system, in this case the altitude, position and attitude of your drone.
I will thoroughly detail and walk you through each of these concepts and techniques and explain down to their fundamental principles, all concepts and subject-specific vocabulary. This course is the ideal beginner, intermediate or advanced learning platform for the mathematics behind engineering systems, the use of MATLAB and SIMULINK in engineering design and PID control. Whatever your background, whether you are a student, an engineer, a sci-fi addict, an amateur roboticist, a drone builder, a computer scientist or a business or sports person, you will master the physics behind an electric car and learn how to implement and control them in SIMULINK by designing powerful PID controllers that bridge the gap between humans and machines!
If you have questions at any point of your progress along the course, do not hesitate to contact me, it will be my pleasure to answer you within 24 hours!
If this sounds like it might interest you, for your personal growth, career or academic endeavours, I strongly encourage you to join! You won't regret it!