System Identification
Systemidentifiering

FRT115F, 7.5 credits

Valid from: Autumn 2014
Decided by: FN1/Anders Gustafsson
Date of establishment: 2015-02-10

General Information

Division: Automatic Control
Course type: Third-cycle course
Teaching language: English

Aim

System identification treats how to construct mathematical models of dynamical systems from measured data. The doctoral student acquires knowledge about the ideas, concepts and theory of system identification. The doctoral student develops the ability to preform system identification experiments and to perform system identification using experimental data.

Goals

Knowledge and Understanding

For a passing grade the doctoral student must know and understand the fundamental ideas of system identification and the theoretical framework.

Competences and Skills

For a passing grade the doctoral student must

• have the ability to plan and execute system identification experiments, choice of input signals and selection of appropriate models and methods.
• demonstrate skills in using the "System Identification Toolbox" and the ability to analyze and evaluate the results of the calculations.

Judgement and Approach

For a passing grade the doctoral student must

• have the ability to judge the appropriate model complexity required for control design.
• have the ability to balance model complexity and efforts required for experiments and analysis.

Course Contents

The mathematical foundations of System Identification. Parametric and non-parametric techniques. Parametrizations and model structures. Parameter estimation. Asymptotic statistical theory. User choices. Experimental design. Choice of model structure. Assessment of the results.

Course Literature

Ljung, L.: System Identification - Theory for the user 2n edition,. Prentice Hall, 1999.
Also Mathworks: System Identification Toolbox.

Instruction Details

Types of instruction: Lectures, seminars, exercises, project. The instruction is a mixture of lectures and seminars. Problems are assigned every week and discussed the next week following the schedule for Ljungs course at ISY in Linköping http://www.rt.isy.liu.se/student/graduate/idkurs/. A project has also to be executed preferably related to the students PhD subject. The doctoral students can collaborate in the project.

Examination Details

Examination formats: Oral exam, written assignments. Evaluation of the weekly problem solving session. An assessment of the project and an oral examination.
Grading scale: Failed, pass
Examiner:

Admission Details

Assumed prior knowledge: Linear systems, probability theory and statistics

Course Occasion Information

Contact and Other Information

Course coordinators: