93850 - Unmanned Systems

Learning outcomes

At the end of the course, the student is knows how to create a mathematical model of an unmanned aircraft and he knows how to design and implements the main attitude and trajectory control systems. Through experimental lab activities, he also gets familiar with the fundamentals of Remote-Piloted Aircraft Systems flight planning and operations.

Course contents

• Unmanned Systems: history and evolution.
• GNC systems design: the Model-Based approach.
• Fixed-wing battery-powered platforms: performance analysis and optimization. Optimal-design configurations.
• Conventional rotary-wing (helicopter) battery-powered platforms: performance analysis and optimization.
• Battery-powered multirotor platforms: performance analysis and optimization. The aerodynamics of propellers conceived for multirotor professional applications. Optimal design configurations. 
• The making of a simulation model: Blade-Element Theory analysis and implementation of multirotor equations of motion in Matlab/Simulink environment. 
• Open-loop and closed-loop analysis of 6DOF multirotor dynamic model.
  
• Guidance, Navigation, and Control systems definition and implementation. Differences between control modes.

Readings/Bibliography

• Brian L. Stevens, Frank L. Lewis, Eric N. Johnson, Aircraft Control and Simulation, Third Edition, John Wiley & Sons, Inc., 2016.
• Peter D. Talbot, et al., A mathematical model of a single main rotor helicopter for piloted simulation, NASA Technical Memorandum (TM) 84281, NASA, 1982. 
  
• J. Gordon Leishman, Principles of Helicopter Aerodynamics, Second Edition, Cambridge Aerospace Series, Cambridge University Press, 2006.
• Gareth D. Padfield, Helicopter Flight Dynamics: The Theory and Application of Flying Qualities and Simulation Modelling, Second Edition, Blackwell Publishing, 2007.
• Donald McLean, Automatic Flight Control Systems, Prentice Hall, 1990.
• Kimon P. Valavanis (Editor), Unmanned Aircraft Systems - The Current State-of-the-Art, Springer, 2013.

Teaching methods

• Class lectures on digital whiteboard (exclusively in-presence).
• Collaborative computer programming in Matlab/Simulink environment.
• Numerical exercises and simulations.
• Eventual educational visits and laboratory activities.

Assessment methods

The exam consists of a single practical and oral session in which the student is requested to:

1) solve a proposed simulation/design task on his own laptop (60 minutes, examples will be provided during the course),

2) answer theoretical questions about the overall course program,

3) discuss the personal simulation model developed during the course (15 minutes). 

Teaching tools

• Digital whiteboard.
• MathWorks products for computer programming.
• Laboratory equipments.
• Unmanned electric platforms.

Office hours

See the website of Emanuele Luigi De Angelis