Table of contents

The course is connected to the following study programs

Learning outcomes

The learning outcome of the course is insight into current research topics within advanced control systems and robotics. The successful candidate will have knowledge of the state-of-the-art within a number of topics related to analysis and design of multivariable and nonlinear systems.

Contents

The course presents a number of selected topics within state-of-the-art in advanced control and robotics research. Emphasis is on multivariable, non-linear systems. The course will contain selected topics from the following list:

  • Nonlinear dynamic modelling of robotic systems (Euler-Lagrange, Newton-Euler)
  • Independent Joint Control and Multivariable Control of Robots
  • Force Control
  • Feedback Linearisation
  • Variable Structure and Adaptive Control, Sliding Mode Control
  • Model Predictive Control (MPC)
  • Adaptive Backstepping Techniques
  • Multivariable Robust Control (H-Infinity)
  • Quantitative Feedback Theory (QFT)
  • Linear Matrix Inequalities (LMI)

Teaching and learning methods

Lectures (8 days). Exercises

Examinations

Portfolio. Individual assessment. Pass/fail.

Information about the content of the portfolio will be given in Canvas by the start of the semester. There will not be arranged a postponed exam for the portfolio.

Student evaluation

The course will be evaluated in accordance with the quality assurance system for education, chapter 4.1.

Offered as a free-standing course

Yes. Subject to availability or capacity.
Last updated from FS (Felles studentsystem) Oct. 15, 2026 3:15:32 PM