Intro to Aerospace Navigation, Control and Flight Simulation

What you’ll learn:
Learn the basics of aircraft longitudinal and lateral flight dynamics and control
Learn how model predictive control can be applied to linear systems
Learn how full 6-DOF flight simulations are developed and visualized from case studies
Develop your own custom flight simulations using Python and FlightGear using UDP communication

Requirements:
No programming experience needed. The assignments will provide a good introduction.
You are requested to install FlightGear v.2020.3.18 or higher, a free open source flight simulator.
You will also need Python with several packages: numpy, scipy, matplotlib, controls toolbox, pandas, flightgear-python
If you do not have FlightGear, you will still learn a lot and be able to complete Assignments 3 to 5, however you’ll miss out on being able to perform cool simulations.

Description:
Important Note:Please go through the first 3 free videos and Assignment 0 to setup Python and FlightGear to be able to run your simulations. There are a lot of Python packages to install along with FlightGear aircraft and scenery. You are strongly suggested to have everything ready prior to committing to the course. Assignment 0 is a test to ensure things are working smoothly – Please download it from GitHub: Vinayak-D: AerospaceGNCUdemyCourseHighlights:Learn the basics of aircraft flight dynamics in six degrees of freedom (6-DOF) and model predictive control from practical examples. Understand and apply the User Datagram Protocol (UDP) communication to build your own flight simulations using data sent to/from Python to FlightGear, a free open source flight simulator. Complete 5 interactive assignments to strengthen your understanding of the subject matter. Obtain thorough knowledge of the aircraft equations of motion, a required concept for jobs in the aerospace industry. Learn how to build full 6-DOF simulations from limited information.Description:The aerospace industry is now at a critical phase. A lot of new technologies are being developed such as supersonic and hypersonic flight, new commercial reusable launch vehicles, as well as small aerial vehicles such as air taxis, drones, and similar machines for personal use. This course serves as an introduction to flight dynamics for the absolute beginner. Complex topics such as the aircraft equations of motion, how rotations can be mathematically represented, and the basics of flight simulations are introduced in a practical manner. Case studies on flight control design using open source information from the F-16 aircraft are also presented. This course introduces the topic of linear control theory, state space representation, and transfer functions.Assignments 0 and 1 get you started with FlightGear and Python interacting together via the UDP protocol, and basic coordinate transforms to convert your 3D location to a point on a map.You will learn quadratic optimization, a fundamental concept in control theory as well as machine learning for all industries ranging from tech to finance.You will implement a quadratic optimization solver using Python in Assignment 2. You will learn how to apply model predictive control for linear systems specifically for flight control applications through Assignments 3 and 4.Finally, Assignment 5 ties everything together, you will visualize a full 6-DOF flight simulation in FlightGear!

Who this course is for:
Anyone interested in aerospace engineering, flight dynamics, control, and building custom simulations.