Automatic Control

Faculty of Engineering, LTH

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FRTN15 - Predictive Control

Prediktiv reglering, 7.5 hp

Syllabus   CEQ   Schedule

Frequently asked questions are collected here.

Personnel 2019



Problem solving sessions and labs

  • Marcus Greiff <>
  • Christian Rosdahl <>


Recommended Prerequisites:

Automatic Control (FRT010), some background in discrete-time signals and systems.


Course Material



Lectures will be held in M:E or M:B on Tuesdays 13.15–15.00 and Thursdays 13.15–15.00 according to the schedule:

Week Date No Contents Ref.
4 22/1 L1 Introduction. Signals & Systems. Real-time Parameter Estimation. Ch. 1, 2, 4
  24/1 L2 Automatic Tuning, Gain Scheduling, Auto-calibration.  Ch. 1
5 29/1 L3 ARMAX models. Pole assignment Model Matching. Optimal Control.  Ch. 5, A, B
  31/1 L4 Pole Assignment. Model matching. Disturbance Models. LQ Control.  Ch. 5, 6
 6 5/2 L5 Optimal Prediction. Optimal Predictive Control. The Kalman Filter. LQG Control.  Ch. 5, 7, 8
  7/2 L6 Adaptive Control  Ch. 9
 7 12/2 L7 Adaptive Control.  Ch. 9
  14/2 L8 Model Predictive Control (MPC)  Ch. 13
8 19/2 L9 Iterative Learning Control (ILC). Iterative Feedback Tuning (IFT).  Ch. 12
  21/2 L10 More Model Predictive Control  Ch. 13
9 26/2 L11 Stability: Lyapunov Theory.  Ch. D
  28/2 L12 Stability: Input-Output Stability. Passivity.  Ch. E
10 5/3 L13 Stochastic Adaptive Control  Ch. 10, 11
  7/3 L14 Implementation. Applications. Summary. Hour for Questions.


  Copies of the lecture slides are available here (the username is "control", you'll also need the fun password mentioned at the lecture).


Some Matlab Code etc

  • ex0.m (Stochastic system, Lecture 2)
  • ex1.m (Correlation and Covariance, Lecture 2)
  • design1.m (Polynomial design Lecture 4)
  • predictor.m (Optimal d-step aheap prediction, Lecture 4)
  • (All matlab code used in Lecture 5, incl the useful rstd.m and dab.m)
  • (All matlab code used in Lecture 6)
  • (All matlab code used in Lecture 7)
  • (All matlab code used in Lecture 8)
  • MPC TOOLS manual (used in Lecture 10)
  • MPC Tools (including the Quad tank and Helicopter examples in Lecture 10)
  • (ILC code used in Lecture 11)


LP3 Fridays 10.15-12.00 or 13.15-15.00 in M:M1:

  • Marcus Greiff (
  • Christian Rosdahl (
 Week  Date   Contents
4 25/1 E1 Simulation of Adaptive Systems.
Notice simulation session in Lab B!
5 1/2 E2 Real-Time Parameter Estimation.
6 8/2 E3 Optimal Prediction. Optimal estimation. Kalman filter.
7 15/2 E4 Adaptive Control.
8 22/2 E5 Model Predictive Control
9 1/3 E6 Iterative Learning Control (ILC)+additional
10 8/3 E7 Stability of Adaptive Schemes, Exam questions


Exercise Materials

    1. Exercise 1 with Notice that this computer exercise is held in Lab B.
    2. Exercise 2 and solutions
    3. Exercise 3 and solutions
    4. Exercise 4 and solutions
    5. Exercise 5 and solutions
    6. Exercise 6 and solutions
    7. Exercise 7: Old Exams (see below) and Questions

Laboratory sessions

Sign up for the laboratory sessions here, and do so at least one day in advance. Note that Lab 1 is now updated, and there is no preparations needed apart from reading the relevant chapters in the course book.

Lab Time Contents Responsible
Lab 1 w.6 Gain Scheduling Marcus Greiff
Lab 2 w.8 Adaptive Control Marcus Greiff
Lab 3 w.9 Predictive Control Christian Rosdahl




Laboratory Materials


Tuesday, March 19, at 14-19 in MA:10A-B.

Old Exams

Home Work Assignments

Please send your solutions by the deadlines to the emails mentioned in the handins. Please use PDF-format when possible. Homework should be handed in individually. Reasonable cooperation is allowed (but not copying other persons handins...).

    • Home Work 3—Model Predictive Control (MPC). Deadline February 24, 2019. Responsible: Christian Rosdahl

Please send your solutions by the deadlines to the emails mentioned in the handins in a PDF-format or to <>. You will get feedback on your solution, and if it needs revision, you will have to submit a revised solution within a week of receiving the feedback. Cooperation is allowed in small groups, but every student needs to submit an individual report for every homework.



The projects will be done individually or in small groups of 2-4 students. A list of project proposal can be found in the project list. You should sign up for a project no later than Friday, March 1. The deadline for the project report is May 3 unless otherwise agreed with the project supervisors. The project should be presented Friday, May 3, at 10:15-12:00 in the seminar room M:2112B of Dept. Automatic Control. All project groups should give an oral presentation of 5-10 minutes. Presence mandatory for students of FRTN15. WELCOME!

Project Groups 2019

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