Syllabus for Automatic Control II

Reglerteknik II

Syllabus

  • 5 credits
  • Course code: 1RT495
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Technology A1N, Embedded Systems A1N

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle

    • G1N: has only upper-secondary level entry requirements
    • G1F: has less than 60 credits in first-cycle course/s as entry requirements
    • G1E: contains specially designed degree project for Higher Education Diploma
    • G2F: has at least 60 credits in first-cycle course/s as entry requirements
    • G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    • GXX: in-depth level of the course cannot be classified

    Second cycle

    • A1N: has only first-cycle course/s as entry requirements
    • A1F: has second-cycle course/s as entry requirements
    • A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    • A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    • AXX: in-depth level of the course cannot be classified

  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2010-03-16
  • Established by:
  • Revised: 2018-08-30
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: Spring 2019
  • Entry requirements:

    120 credits including Automatic Control I. Proficiency in English equivalent to the Swedish upper secondary course English 6.

  • Responsible department: Department of Information Technology

Learning outcomes

On completion of the course, the student should be able to:

  • determine relations between multivariable dynamic models in form of state space models and transfer functions
  • analyse multivariable dynamic systems with respect to stability, sensitivity for disturbances, statistical properties, and controllability and observability
  • analyse dynamic systems influenced by noise, and to determine stationary variances for given linear models
  • design optimal observers (Kalman filters)
  • design controllers for linear multivariable systems based on linear quadratic (LQ) control
  • account for the principles behind model predictive control (MPC)
  • evaluate controllers in laboratory work on real processes

Content

Mathematical description of linear multivariable systems in continuous and discrete time. Controllability and observability. Stability. Description of disturbances and their effects. Controller synthesis using linear quadratic theory and the separation theorem. Model predictive control.

Instruction

Lectures, problem solving sessions, tutorials and laboratory work. Guest lecture. Non-compulsory homework assignments.

Assessment

Written examination at the end of the course (4 credits). Passed laboratory course is also required (1 credit).

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Syllabus Revisions

Reading list

Reading list

Applies from: Spring 2019

Some titles may be available electronically through the University library.

  • Glad, Torkel; Ljung, Lennart Reglerteori : flervariabla och olinjära metoder

    2. uppl.: Lund: Studentlitteratur, 2003

    Find in the library

    Mandatory

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