Remotely piloted airplane systems

Course guarantor:

Pavel Pačes

Lecturer:

Pavel Pačes

Tutor:

Pavel Pačes

Supervisor:

Department of Aerospace Engineering

Synopsis:

The course describes sensor equipment, electronic control system of unmanned aerial vehicles and systems for data transmission. We also focus on algorithms used to control these resources in autonomous mode.

Requirements:

Syllabus of lectures:

1. Integrated modular avionics - its development, standardization, architecture and use (A380, B787).

2. Programming in Matlab / Octave / Scilab environment - use of the system.

3. Programming of network communication and interaction with xPlane / FlightGear simulator systems.

4. Parallel programming and processes - control of several vehicles.

5. Artificial intelligence and representation of space in memory.

6. Artificial intelligence and state space searching.

7. Principles of cooperation of unmanned aerial vehicles

8. Radio means of communication - principles, physical layer, requirements and limitations.

9. Control elements of unmanned systems, sensors, analysis of control SW.

10. Bus and interface for data collection.

11. Parallel systems and principles of transfer of control in case of failure.

12. Introduction to machine learning, probability and neural networks for recognition.

13. Integration of unmanned aerial vehicles into air traffic control from the point of view of legislation.

Syllabus of tutorials:

Laboratory exercises are designed as a consultation time for students working on a semester work, which is focused on the implementation of a selected part of the flight control of a remotely controlled device, or on the implementation of a selected algorithm of artificial intelligence.

Study Objective:

The subject will introduce students into the technology used on the unmanned aerial vehicles with special attention to sensors, the required precision for the safe flight and the ability to maintain stabilisation. These topics will be covered in details: calibration issues and specific problems with inertial sensors, magnetometer and data fusion algorithms. The topics discussed will be solved in the exercises in the individual tasks on simplified examples.

Study materials:

Cary R. Spitzer: The Avionics Handbook, CRC Press, 2007, ISBN: 978-0-84938-348-9

Jitendra R. Raol: Multi-Sensor Data Fusion, CRC Press, 2009, ISBN 9781439800034.

Erik Blasch, DRDC Valcartier, Eloi Bosse, DRDC Valcartier, Dale Lambert: High-Level Information Fusion Management and Systems Design, Artech House, 2012, ISBN: 978-1-60807-151-7.

Moir I., Seabridge A.: Aircraft systems, Wiley 2008, ISBN: 978-0-470-05996-8

Tooley M., Wyatt D.: Aircraft Electrical and Electronic Systems - Principles, Operation and Maintenance. Elsevier 2009

Rogers R. M.: Applied mathematics in integrated navigation systems, 3rd ed., AIAA 2007, ISBN: 978-1-56347-927-4

M. S. Grewal and A. P. Andrews. Kalman Filtering: Theory and Practice using MATLAB. John Wiley & Sons, 2011.

Note:

Time-table for winter semester 2024/2025:

	06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
Tue
Wed
Thu	roomKN:A-213 Pačes P. 09:00–10:30 (lecture parallel1) Karlovo nám. roomKN:A-213 Pačes P. 10:45–12:15 (parallel nr.1) Karlovo nám.
Fri

Time-table for summer semester 2024/2025:

Time-table is not available yet

The course is a part of the following study plans: