Introduction to Quadrotors and Control Theory
What you'll learn
- to model the dynamics of a quadrotor drone
- to build flight stabilization algorithms based on PID controllers
Requirements
- Python programming
- Basic elements of Linear Algebra
- Basic knowledge of Differential Equations
- Familiarity with highschool Physics
Description
This course takes you through the basic elements of building a physically based quadrotor drone simulation, and introduces elements of control theory, such as the feedback loop and PID controllers. You will learn about representing rotation in 3D space using rotation matrices, quaternions and Euler angles. You will learn to implement a discrete-time PID controller, and an entire PID-based controller structure for attitude and position control for non-aggresive flight. You will be provided with a reference implementation in Python to experiment with.
Who this course is for:
- Students interested in Quadrotors
- Students interested in Rigid Body Motion
- Students interested in PIDs
- Students interested in drones
Instructor
- 4.0 Instructor Rating
- 37 Reviews
- 248 Students
- 1 Course
I am a Control Engineer with a focus on Mathematical Modeling and Software Simulation, and I have an academic background.
As a control engineer, I seek to understand physical systems in terms of inputs, outputs and feedback loops, to characterize stability and other system-wide properties, and explore possibilities for control or optimization.
I work daily with various aspects of software engineering (development, maintenance, testing) and applied mathematics (statistics, differential equations, optimization )
I have experience with:
- 3D motion and flight, such as rigid body dynamics, motion sensors and their properties (gyroscopes and accelerometers), navigation concepts (e.g. Kalman filter, trajectory generation), aerodynamic concepts, from master and post-doc projects .
- The energy and power balancing problem, and demand response from my PhD work
- Large C/C++ projects, Python scripting