Intro to Aerospace Navigation, Control and Flight Simulation

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Vinayak Deshpande

3:14:52

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1. Getting Started

1. Course Overview.mp4

05:40

2.1 Download FlightGear.html

2.2 Download FlightGear Aircraft.html

2. Installing and Configuring FlightGear.mp4

15:44

3.1 Conda environments.html

3.2 Download all assignments here.html

3.3 FlightGear Python Interface.html

3.4 Python Control Systems Library.html

3. Configuring Python.mp4

06:07

4.1 DOWNLOAD ASSIGNMENTS HERE.html

4. Assignment 0 Testing (IMPORTANT!).mp4

09:47

2. Coordinate Transformations

1. Earth Centered Earth Fixed (ECEF) Frame.mp4

06:50

2. Latitude Longitude Altitude (LLA) and North East Down (NED) Frames.mp4

06:16

3.1 NEDLLAECEF Transformations.pdf

3. Converting between LLA and NED Frames.mp4

08:28

4. Assignment 1 Frame Conversions (and Solution).mp4

11:53

3. Linear Systems and State Space Control Theory

1. State Space Representation.mp4

16:52

2. Introduction to Optimization.mp4

10:48

3. Optimization Algorithm.mp4

06:44

4. Assignment 2 Optimization (and Solution).mp4

06:41

5. Model Predictive Control Theory.mp4

07:24

6. Model Predictive Control Framework.mp4

04:03

7. Assignment 3 MPC Framework in Python (and Solution).mp4

10:21

4. Aircraft Longitudinal Flight Dynamics and Control

1. Understanding Flight Dynamics.mp4

03:42

2. The Aircraft Equations of Motion.mp4

05:57

3. Aircraft Longitudinal Dynamics.mp4

04:17

4. Aircraft Longitudinal Control.mp4

06:14

5. Assignment 4 Aircraft Longitudinal Control and FlightGear Simulation!.mp4

16:11

5. Full Flight Simulations

1.1 paper.pdf

1. Lateral Dynamics and Full 6-DOF simulations.mp4

05:08

2. Mathematical Model of the F-16 Aircraft.mp4

06:12

3. Case Study Advanced Fighter Technology F-16 Multivariable Flight Control.mp4

05:35

4. Final Assignment Full 6-DOF FlightGear and Python Simulation!.mp4

07:29

5. Conclusion.mp4

00:29

Description

Interested in building your own custom flight control and simulation algorithms? Then check out this course!

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

Who is this for?

Anyone interested in aerospace engineering, flight dynamics, control, and building custom simulations.

What You Need to Know?

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.

More details

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, repo: AerospaceGNCUdemyCourse - see the course preview video or Lecture 3 (Configuring Python) for the download link.

Highlights:
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)Â 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.

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Control Systems

Vinayak Deshpande

Instructor's Courses

I have a masters degree in Mechanical Engineering in Control Theory and Simulation with 3 conference publications in the field of Model Predictive Control. My Bachelor's degree was also in Mechanical Engineering. I currently work as a Development Engineer at a defense contractor in Canada, building simulations and model based design architecture in Matlab, Simulink and C++. I have over 3 years of experience with modeling and simulation of mechanical and aerospace systems. I have always had a strong passion for teaching ever since I started my YouTube Channel in 2016. My mission statement is to deliver high quality training material on complex engineering topics.

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