One of the greatest transformations that we will see in the next couple of decades is going to be the advent of autonomous drones. While being used extensively already, the applications of quadcopters will only grow in time. Drones will be used in delivery services, entertainment, medicine, military, rescue, structural quality inspection - places that people cannot reach easily, and in many other fields.
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One of the greatest transformations that we will see in the next couple of decades is going to be the advent of autonomous drones. While being used extensively already, the applications of quadcopters will only grow in time. Drones will be used in delivery services, entertainment, medicine, military, rescue, structural quality inspection - places that people cannot reach easily, and in many other fields.
One of the greatest transformations that we will see in the next couple of decades is going to be the advent of autonomous drones. While being used extensively already, the applications of quadcopters will only grow in time. Drones will be used in delivery services, entertainment, medicine, military, rescue, structural quality inspection - places that people cannot reach easily, and in many other fields.
In many cases, there will be a predefined trajectory in a 3D space that the UAV needs to follow without human help. In fact, humans might simply give a simple command for the drone to go somewhere, and then, a specific trajectory will be generated by a computer in that direction and the UAV's control algorithms will need to determine EXACTLY how fast each rotor should turn in order to make the drone follow that trajectory with high-degree precision.
And that's what this course is all about - its about
In this course, you will receive a full package when it comes to learning about how to model and control a UAV drone and make it follow a trajectory in a 3D environment. Not only you will learn how to model a UAV system mathematically by deriving the equations of motion using the principles of 3D Dynamics, but you will also be exposed to some of the most powerful control techniques out there such as Model Predictive Control and feedback linearization.
In 3D dynamics, you will learn the fundamental math and physics behind the UAV quadcopter drone modelling. You will learn how to describe the position and orientation of a UAV quadcopter drone in a 3D space using rotation and transfer matrices, Newton - Euler 6 Degree of Freedom equations of motion, widely used Runge - Kutta integrator in engineering and propeller dynamics.
In the end of the course, I will also explain to you the code in the Python simulator.
Understanding the material in this course fundamentally, being able to quantify it mathematically, and knowing how to apply it using coding - that will give you an advantage in your engineering career that you cannot even imagine yet. It will give you a competitive edge that you need in the labor market.
I'm very excited to start working with you. Take a look at some of my free preview videos, and if you like what you see, then ENROLL in the course, and let's get started right now.
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What's inside
Learning objectives
- Mathematical modelling of a uav quadcopter drone
- Obtaining kinematic equations: rotation & transfer matrices
- Obtaining newton-euler 6 dof dynamic equations of motion with rotating frames
- Going from equations of motion to a uav specific state-space equations
- Understanding the gyroscopic effect & applying it to the uav model
- Understanding the runge-kutta integrator and applying it to the uav model
- Mastering & applying model predictive control algorithm to the uav
- Mastering & applying a feedback linearization controller to the uav
- Combining model predictive control and feedback linearization in one global controller
- Simulating the drone's trajectory tracking in python using the mpc and feedback linearization controller
- Mathematical modelling of a uav quadcopter drone
- Obtaining kinematic equations: rotation & transfer matrices
- Obtaining newton-euler 6 dof dynamic equations of motion with rotating frames
- Going from equations of motion to a uav specific state-space equations
- Understanding the gyroscopic effect & applying it to the uav model
- Understanding the runge-kutta integrator and applying it to the uav model
- Mastering & applying model predictive control algorithm to the uav
- Mastering & applying a feedback linearization controller to the uav
- Combining model predictive control and feedback linearization in one global controller
- Simulating the drone's trajectory tracking in python using the mpc and feedback linearization controller
Syllabus
You will learn relevant drone architecture necessary for control engineering
Introduction
UAV configuration + inertial VS body frame
Inputs and outputs of a 6 Degree of Freedom UAV drone
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Syllabus
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Activities
Review basic linear algebra
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Review basic linear algebra to strengthen your mathematical foundation for the course.
Browse courses on
Linear Algebra
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Go over your notes from a previous linear algebra course.
-
Solve practice problems.
-
Take an online refresher course.
-
Watch video tutorials on linear algebra.
Mentor other students in the course
Show steps
Offer support and guidance to other students in the course to reinforce your own understanding of the material and help others succeed.
Show steps
-
Identify a student who is struggling with the material.
-
Offer to help the student by answering their questions or providing additional explanations.
-
Meet with the student regularly to provide support and guidance.
Review the book 'Control of Nonlinear Systems' by Khalil
Show steps
Read the book 'Control of Nonlinear Systems' by Khalil to gain a deeper understanding of nonlinear control theory and its applications.
View
Control Systems: An Introduction
on Amazon
Show steps
-
Purchase or borrow the book.
-
Read the book carefully, taking notes as you go.
-
Try to solve the exercises at the end of each chapter.
Five other activities
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Show all eight activities
Solve Newton-Euler equations
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Practice solving Newton-Euler equations to reinforce your understanding of rigid body dynamics and prepare for the course.
Show steps
-
Review the equations of motion for a rigid body.
-
Choose a simple rigid body system.
-
Apply the Newton-Euler equations to the system to determine its motion.
Follow a tutorial on feedback linearization
Show steps
Watch a tutorial on feedback linearization to enhance your understanding of the technique and improve your ability to design controllers for nonlinear systems.
Show steps
-
Find a tutorial on feedback linearization that is appropriate for your skill level.
-
Watch the tutorial and take notes.
-
Try to apply the technique to a simple nonlinear system.
Create a video tutorial on the use of the Runge-Kutta integrator
Show steps
Create a video tutorial on the use of the Runge-Kutta integrator to reinforce your understanding of numerical methods and improve your ability to solve differential equations.
Browse courses on
Numerical Methods
Show steps
-
Review the theory behind the Runge-Kutta integrator.
-
Choose a software package for creating the video tutorial.
-
Record the video tutorial, explaining the concepts clearly and concisely.
Attend a workshop on Model Predictive Control
Show steps
Attend a workshop on Model Predictive Control to learn about the technique and how to apply it to real-world problems.
Show steps
-
Find a workshop on Model Predictive Control that fits your schedule and interests.
-
Register for the workshop.
-
Attend the workshop and participate actively.
Build a simple quadcopter drone
Show steps
Build a simple quadcopter drone to apply your knowledge of control systems and robotics and gain hands-on experience.
Browse courses on
Robotics
Show steps
-
Gather the necessary materials.
-
Assemble the drone.
-
Program the drone to fly.
Review basic linear algebra
Show steps
Review basic linear algebra to strengthen your mathematical foundation for the course.
Browse courses on
Linear Algebra
Show steps
- Go over your notes from a previous linear algebra course.
- Solve practice problems.
- Take an online refresher course.
- Watch video tutorials on linear algebra.
Mentor other students in the course
Show steps
Offer support and guidance to other students in the course to reinforce your own understanding of the material and help others succeed.
Show steps
- Identify a student who is struggling with the material.
- Offer to help the student by answering their questions or providing additional explanations.
- Meet with the student regularly to provide support and guidance.
Review the book 'Control of Nonlinear Systems' by Khalil
Show steps
Read the book 'Control of Nonlinear Systems' by Khalil to gain a deeper understanding of nonlinear control theory and its applications.
View
Control Systems: An Introduction
on Amazon
Show steps
- Purchase or borrow the book.
- Read the book carefully, taking notes as you go.
- Try to solve the exercises at the end of each chapter.
Solve Newton-Euler equations
Show steps
Practice solving Newton-Euler equations to reinforce your understanding of rigid body dynamics and prepare for the course.
Show steps
- Review the equations of motion for a rigid body.
- Choose a simple rigid body system.
- Apply the Newton-Euler equations to the system to determine its motion.
Follow a tutorial on feedback linearization
Show steps
Watch a tutorial on feedback linearization to enhance your understanding of the technique and improve your ability to design controllers for nonlinear systems.
Show steps
- Find a tutorial on feedback linearization that is appropriate for your skill level.
- Watch the tutorial and take notes.
- Try to apply the technique to a simple nonlinear system.
Create a video tutorial on the use of the Runge-Kutta integrator
Show steps
Create a video tutorial on the use of the Runge-Kutta integrator to reinforce your understanding of numerical methods and improve your ability to solve differential equations.
Browse courses on
Numerical Methods
Show steps
- Review the theory behind the Runge-Kutta integrator.
- Choose a software package for creating the video tutorial.
- Record the video tutorial, explaining the concepts clearly and concisely.
Attend a workshop on Model Predictive Control
Show steps
Attend a workshop on Model Predictive Control to learn about the technique and how to apply it to real-world problems.
Show steps
- Find a workshop on Model Predictive Control that fits your schedule and interests.
- Register for the workshop.
- Attend the workshop and participate actively.
Build a simple quadcopter drone
Show steps
Build a simple quadcopter drone to apply your knowledge of control systems and robotics and gain hands-on experience.
Browse courses on
Robotics
Show steps
- Gather the necessary materials.
- Assemble the drone.
- Program the drone to fly.
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