EL1010 Automatic Control, General Course 6.0 credits

Reglerteknik, allmän kurs

An introductory course on control systems. It provides the students with the basic engineering knowledge of dynamic systems and feedback

Show course information based on the chosen semester and course offering:

Offering and execution

No offering selected

Select the semester and course offering above to get information from the correct course syllabus and course offering.

Course information

Content and learning outcomes

Course contents *

The course covers how feedback influences properties of dynamic system such as stability, speed of response, sensitivity and robustness. The course contains analysis and design of feedback systems with regard to these properties. In particular, the following is studied

  • basic concepts and problems: Application examples of automatic control in society, representation of dynamic system, in and output signals, differentia equation models, Laplace transform, transfer functions, block diagrams, step response, poles, zeros, linearisation and state space models
  • analysis of feedback systems: stability, root locus, the Nyquist criterion, Nyquist and Bode diagrams, speed of response, error coefficients, sensitivity and robustness
  • design of control systems with one input signal and one output signal: specifications, PID-controllers, compensation in the frequency domain, feed-forward control, time delays, state feedback, observers and pole placement
  • implementation: choice of sampling time, anti alias filters and discretisation of controllers
  • control terminology in Swedish and English.

Intended learning outcomes *

After passing the course, the student should be able to

  • formulate basic theory and definitions of important concepts in general automatic control
  • apply analysis and design methods in general automatic control

Course Disposition

No information inserted

Literature and preparations

Specific prerequisites *

General entry requirements.

Recommended prerequisites

SF1629 Differentialekvationer och transformer II, eller SF1634 Differentialekvationer II, eller EQ1110 Tidskontinuerliga signaler och system, or equivalent


No information inserted


No information inserted

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale *

A, B, C, D, E, FX, F

Examination *

  • LABA - Lab 1, 1.0 credits, Grading scale: P, F
  • LABB - Lab 2, 2.0 credits, Grading scale: P, F
  • LABC - Computer Project, 2.0 credits, Grading scale: P, F
  • TENA - Exam, 1.0 credits, Grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Other requirements for final grade *


Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted


Henrik Sandberg

Ethical approach *

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web EL1010

Offered by

EECS/Intelligent Systems

Main field of study *


Education cycle *

First cycle

Add-on studies

  • EL1820 Modellering av dynamiska system
  • EL2620 Olinjär reglering
  • EL2520Reglerteknik fk
  • EL2421 Reglerteknik, projektkurs
  • EL2450 Hybrida och inbyggda reglersystem
  • EL2745 Principles of Wireless Sensor Networks
  • EL2700 Model Predictive Control
  • EL2800 Stochastic Control and Optimization


Henrik Sandberg

Supplementary information

In this course, the EECS code of honor applies, see: