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Graduate courses

Departments' graduate courses for PhD-students.


Syllabus for

Academic year
ERE033 - Automatic control  
Syllabus adopted 2019-02-21 by Head of Programme (or corresponding)
Owner: TKMAS
7,5 Credits
Grading: TH - Five, Four, Three, Fail
Education cycle: First-cycle
Major subject: Automation and Mechatronics Engineering, Electrical Engineering

Teaching language: Swedish
Application code: 55111
Open for exchange students: No
Block schedule: D
Only students with the course round in the programme plan

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0107 Design exercise + laboratory 2,0c Grading: UG   2,0c    
0207 Examination 5,5c Grading: TH   5,5c   17 Jan 2020 am SB_MU   02 May 2020 am DIST   21 Aug 2020 am J

In programs



Knut Åkesson

  Go to Course Homepage


ERE031   Automatic control ERE032   Automatic control


In order to be eligible for a first cycle course the applicant needs to fulfil the general and specific entry requirements of the programme(s) that has the course included in the study programme.

Course specific prerequisites

Mathematical concepts that the student must master before starting the course are:

- Complex numbers
- Linear algebra
- Taylor expansions
- Ordinary differential equations

It is also assumed that the student has basic knowledge about the fundamental physical relations that are necessary to formulate energy, force and material balances.


The aim of the course is to help mechanical engineering students to understand how control might be used to develop and implement control function for mechanical systems. Furthermore the aim of the course is to widen the student s perspective on technical systems by understanding how mechanics, electronics, computers, and control interact and how this might be used to improve and develop new products that offer new functionality and increased performance.

The course uses knowledge from the fundamental courses in mathematics, mechanics and computer programming and will prepare the student for further studies in subjects where fundamental knowledge in dynamical systems and control engineering is required.

Learning outcomes (after completion of the course the student should be able to)

show basic knowledge in control engineering analysis and design methods. This knowledge could be used to systematically solve basic control problems. More specifically, the student should be able to:
  • Define the control problem.
  • Define feedback and feed forward.
  • Describe and explain the most important properties of linear systems.
  • Describe how the frequency content of a signal could be analysed.
  • Formulate a dynamic model for basic mechanical, electrical and chemical systems.
  • Explain the possibilities and limitations of state-space models and transfer functions.
  • Transform between state-space models and transfers functions, when possible.
  • Compute linear approximations of non-linear models and understand the limitations of the non-linear model.
  • Analyse the stability properties of linear dynamic systems and analyse the closed-loop systems stability properties based upon the Nyquist-criteria.
  • Explain how feedback and feed-forward can be used to decrease the influence from process- and measurements disturbances and parameter variations in the controlled process, and also explain the limitations of feedback and feed forward.
  • Design controllers that satisfy specifications, such as performance, robustness-, and stability margin specifications.
  • Analyse and evaluate different controller structures, mainly P, PI, PD, PID and state-feedback controllers.
  • Implement the designed controller in a computer and understand sampling and its consequences.
  • Use modern computer tools to facilitate analysis, design, and evaluation of dynamical systems.


Introduction: Examples of control problems, dynamic systems, feedback and feed-forward, compensation of parameter variations, process and measurement disturbances.

Fundamentals of signal theory: Frequency analysis of signals. Dynamic models: Differential equations, Laplace transforms, transfer functions, block diagrams, impulse response function, frequency response, transient and frequency analysis, Bode diagrams. Principles for building dynamic models for engineering systems. State space models, non-linear systems, linearization.

Analysis of feedback systems: Stability, Nyquist criteria, stability margins, sensitivity. Performance, transient and stationary properties, specification in both time and frequency domain.

Design of control systems: Basic principles for control design, possibilities and limitations. Design of PI- and PID controllers, cascade control and feed-forward. State space design.

Implementation: Implementation of a controller in a computer. Sampling and its consequences. Translation of continuous controllers to discrete controllers.

Laboratory experiments and assignments: Modelling, simulation, control design. and implementation of a balancing robot. The students have free access to the robot throughout the course. The presentation of the labs/hand-ins is done through three hand-ins that are presented in written reports as well as oral presentations. The modelling, simulation and control design parts are done with help of Matlab/Simulink, The implementation part is done in using the Arduino development environment.


Teaching is in the form of lectures, group exercises and three home assignments (modeling, simulation, control, and implementation of a balancing robot)


B Lennartson: Reglerteknikens grunder, Studentlitteratur. (In Swedish) and Reglerteknik M (Lecture notes by Bo Egardt and Knut Åkesson, In Swedish). Reglerteknikens grunder - övningstal, compendium (In Swedish). Reglerteknik M3 och D3 - formelsamling, compendium (In Swedish). Other material, see course home page.

Examination including compulsory elements

Written exam and passed assignments.

Published: Wed 26 Feb 2020.