Course syllabus

Prediktiv reglering
Predictive Control

FRTN15, 7,5 credits, A (Second Cycle)

Valid for: 2019/20
Decided by: PLED F/Pi
Date of Decision: 2019-03-26

General Information

Elective for: BME4, C4, D4-ssr, D4-mai, E4-ra, F4, F4-r, F4-mai, 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 about design of control systems that include predictive, adaptive and learning algorithms for control of time-variable and partially unknown processes with disturbances, including stability and interaction between control and identification.

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

Real-time identification, Recursive identification, Automatic controller tuning, Gain scheduling, Automatic calibration, Discrete-time linear systems, Pole-placement, Model reference system, Disturbance models, Optimal prediction, Optimal model-based predictive control, Adaptive control, Self-tuning control, Stochastic adaptive control, Model reference adaptive control, Stability, Passivity, Robustness, Model-predictive control, Iterative learning control, Iterative controller tuning, Applications and software

Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Written exam (5 hours), project, three laboratory exercises, three hand-in problems. In the case of less than 5 registered students, the retake exams 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: 0116. Name: Examination.
Credits: 5. Grading scale: TH. Assessment: Passed exam
Code: 0216. Name: Laboratory Work 1.
Credits: 0,5. Grading scale: UG. Assessment: Preparation exercises and approved participation in the laboratory
Code: 0316. Name: Laboratory Work 2.
Credits: 0,5. Grading scale: UG. Assessment: Preparation exercises and approved participation in the laboratory
Code: 0416. Name: Laboratory Work 3.
Credits: 0,5. Grading scale: UG. Assessment: Preparation exercises and approved participation in the laboratory
Code: 0516. Name: Project Work.
Credits: 1. Grading scale: UG. Assessment: Written report and oral presentation
Code: 0616. Name: Hand-in Problem 1.
Credits: 0. Grading scale: UG.
Code: 0716. Name: Hand-in Problem 2.
Credits: 0. Grading scale: UG.
Code: 0816. Name: Hand-in Problem 3.
Credits: 0. Grading scale: UG.

Admission

Required prior knowledge: FRTF05 Automatic Control, Basic Course.
The number of participants is limited to: No

Reading list

Contact and other information

Course coordinator: Rolf Johansson, rolf.johansson@control.lth.se
Director of studies: Anton Cervin, anton.cervin@control.lth.se
Course homepage: http://www.control.lth.se/course/FRTN15