Course syllabus

Systemidentifiering
System Identification

FRTN35, 7,5 credits, A (Second Cycle)

Valid for: 2018/19
Decided by: PLED F/Pi
Date of Decision: 2018-03-23

General Information

Elective for: BME5-sbh, C5-ssr, D5-ssr, E4-ss, E4-ra, F4, F4-r, Pi4-ssr
Language of instruction: The course will be given in English on demand

Aim

The aim of the course is to provide advanced knowledge and skills in mathematical modeling based on measurement data, including model structure selection, parameter estimation, model validation, prediction, simulation, and control.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

Competences and skills
For a passing grade the student must

Judgement and approach
For a passing grade the student must

Contents

Identification is a relevant topic for everyone that is working with analysis of experimental data and mathematical modeling. The topics of identification include measurement collection, signal conditioning, model selection, parameter estimation, and mathematical modeling. The course primarily covers physical models and dynamical models represented as differential equations, transfer functions, and difference equations. Identification is important in control, where mathematical models play an important role in decision-making, prediction, control, simulation, and optimization. Many control design methods assume the existence of transfer functions that describe the controlled process. The derivation of these transfer functions is one of the tasks of identification.

Lectures: Transient analysis; Spectral methods; Frequency analysis; Linear regression; Interactive programs; Model parameterizations; Prediction error methods; Instrument variable methods: Real-time identification; Recursive methods; Continuous-time models, Identification in closed loop; Structure selection; Model validation; Experiment design; Model reduction; Partitioned models; 2D-methods; Nonlinear systems; Subspace methods;

Laboratories: Frequency analysis, Interactive identification, Identification for control

Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Written exam (5 hours), project, three hand-in problem sets, three laboratory exercises, In the case of less than 5 registered students, the second and third exam may be given in oral form.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Parts
Code: 0117. Name: Hand-in Problem 1.
Credits: 0. Grading scale: UG.
Code: 0217. Name: Hand-in Problem 2.
Credits: 0. Grading scale: UG.
Code: 0317. Name: Hand-in Problem 3.
Credits: 0. Grading scale: UG.
Code: 0417. Name: Examination.
Credits: 5. Grading scale: TH. Assessment: Passed exam
Code: 0517. Name: Laboratory Work 1.
Credits: 0,5. Grading scale: UG. Assessment: Preparation exercises and approved participation in laboratory
Code: 0617. Name: Laboratory Work 2.
Credits: 0,5. Grading scale: UG. Assessment: Preparation exercises and approved participation in laboratory
Code: 0717. Name: Laboratory Work 3.
Credits: 0,5. Grading scale: UG. Assessment: Preparation exercises and approved participation in laboratory
Code: 0817. Name: Project Work.
Credits: 1. Grading scale: UG. Assessment: Written report and oral presentation

Admission

Required prior knowledge: FRTF05 Automatic Control, Basic Course, FMSF10 Stationary Stochastic Processes.
The number of participants is limited to: No
The course overlaps following course/s: FRT041

Reading list

Contact and other information

Course coordinator: Professor Rolf Johansson, Rolf.Johansson@control.lth.se
Director of studies: Karl-Erik Årzén, karlerik@control.lth.se
Course homepage: http://www.control.lth.se/Education/EngineeringProgram/FRTN35.html