Advanced control of autonomous systems

Higher education teachers: Klančar Gregor
Collaborators: Blažič Sašo
Credits: 5
Subject code: 64836

Subject description


  • Finished programme recommended from natural scientist field.

Content (Syllabus outline):

  • Introduction to autonomous systems – mobile systems, unmanned aerial vehicles, space crafts.
  • Methods for localisation and mapping, simultaneous localisation and mapping, extended Kalman filter, position, orientation and feature estimation methods - particle filter.
  • Higher level control – strategies of multi-agent systems control.
  • Path planning – the principle of optimality, path optimisation with constraints (obstacle avoiding, nonholonomity, dynamic constraints, actuator constraints), satellite orbits.
  • Optimal control in the presence of disturbances.
  • Frequency domain robust control design methods.
  • Trajectory tracking control of autonomous systems.
  • Control of autonomous systems to the final state.
  • Adaptive control of autonomous systems.
  • Matrix inequality control of autonomous systems.

Objectives and competences:

  • to present problems of autonomous systems control,
  • to present methods of localisation and mapping,
  • to present problems of higher level control,
  • to present problems of optimal and adaptive control of autonomous systems,
  • to present the tools for robust control of autonomous systems.

Intended learning outcomes:

  • basic knowledge from autonomous mobile systems and multiagent systems,
  • advanced approaches in autonomous system control,
  • use of obtained knowledge at project work.

Learning and teaching methods:

  • Lectures,
  • Seminar work.

Study materials

  1. Gregory Dudek, Michael Jenkin: Computational Principles of Mobile Robotics, Cambridge University Press, New York, 2010.
  2. Howie Choset, Kevin M. Lynch, Seth Hutchinson, George A. Kantor, Wolfram Burgard, Lydia E. Kavraki, Sebastian Thrun, Principles of Robot Motion: Theory, Algorithms, and Implementations (Intelligent Robotics and Autonomous Agents series), MIT Press, Cambridge, 2005.
  3. Sebastian Thrun, Wolfram Burgard, Dieter Fox: Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series), MIT Press, Cambridge, 2006.
  4. Michael Wooldridge: An Introduction to MultiAgent Systems, Second Edition, John Wiley & Sons, Chichester, England, 2009.
  5. J. Andrade-Cetto, A. Sanfeliu, Environment Learning for Indoor Mobile Robots, Springer, 2006.
  6. G. Balas, R. Chiang, A. Packard, M. Safonov, Robust Control Toolbox 3, User’s Guide, MathWorks, 2008
  7. K. J. Åström, B. Wittenmark, Adaptive Control, Second Edition, Addison-Wesley Publishing Company, Inc., Reading, 1995.