Automatic Control I

5 credits

Syllabus, Bachelor's level, 1RT490

A revised version of the syllabus is available.
Education cycle
First cycle
Main field(s) of study and in-depth level
Sociotechnical Systems G2F, Technology G2F
Grading system
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
Finalised by
The Faculty Board of Science and Technology, 7 August 2012
Responsible department
Department of Information Technology

Entry requirements

60 credits science/technology including Single variable calculus. Linear algebra II. Transform methods.

Learning outcomes

Students who pass the course should be able to

  • define basic concepts in automatic control
  • determine relations between models of linear dynamic systems in form of differential equations, state space models, transient responses, transfer functions and frequency responses
  • analyse linear systems with respect to stability, steady state properties, controllability and observability, and fastness and damping
  • evaluate closed loop systems with respect to stability, as well as robustness against and sensitivity for model errors and disturbances
  • interpret and apply graphical methods and tools like block diagrams, root locus, Bode and Nyquist diagrams
  • understand the function of simple controllers (PID controllers, lead-lag filters, state feedback) and controller structures (feedforward and cascade control)
  • design simple controllers from given specifications
  • understand and design observers for estimating the states in state space models


Modelling and mathematical description of dynamic systems in the time and frequency domain:

Impulse response, step response, transfer function, Bode and Nyquist diagrams, state space description. Estimation of states using observers. Methods for stability analysis including the Nyquist criterion.

Control strategies:

PID controller, lead-lag design, state space feedback. Robustness of feedback systems. Specification and synthesis of control systems.

Laboratory work:

  • Computer aided design, simulation and analysis using the program package MATLAB.
  • Laboratory experiments.


Lectures, problem solving sessions and laboratory work. Guest lecture.


Written examination at the end of the course. Passed laboratory course is also required.