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S-114.4220 Research Seminar on Computational Science

The topic of the course in fall 2007 is

Stochastic and Adaptive Control of Uncertain Systems (5 p) L V

Topic of the seminar is automatic control of uncertain dynamic systems, where a control signal is generated based on observations made from the system and the control signal is used for actively changing the behaviour of the system in order to reach a certain predefined goal. Examples of such control tasks are guidance of a spacecraft, control of a chemical process and steering of a mobile robot.

In the seminar, the purpose is:

  1. to present a review of optimal control, optimal estimation and stochastic control. In these classical approaches, the uncertainties are modeled with random processes and controls are selected to optimize certain model criteria either using variational calculus, or Hamilton-Jacobi-Bellman equations and Bayesian decision theory.
  2. to present review of adaptive and learning control approaches. In these methods, either the value functions (cost-to-go functions) are directly optimized based on a model or some other means are used for adapting the model to the observed environment.
  3. to find the connection between the above two approaches and the connection to the classical pole placement based control design methods.
Dr.Tech. Simo Särkkä, Ph.D. Tuomas Lukka
Basics of probability theory, differential equations, matrix algebra and Bayesian inference. Basic knowledge or ability to learn to use Matlab is needed for completing the exercise.
Place and time
The seminars take place on Mondays at 12:15 in Innopoli 2, B317 (the seminar room of Laboratory of computational engineering, see map). The first lecture is 17.09.2007.
Course Registration
Please register for the course by sending email to Remember to mention the student id. If you have an suggestion for the topic of your presentation, you may mention it in the email also.
English if at least one English speaking participant.


Course requirements:

Control engineering and optimal control:
Stochastic optimal control and estimation:
Approximate dynamic programming:
Adaptive control:

Potential topics of presentations include, but are not limited to:


Date Talker Subject Download
17.9. Simo Särkkä Overview of the Topic PDF slides
24.9. Simo Särkkä Introduction to Classical, Optimal and Stochastic Control PDF slides
1.10. Tuomas Lukka Introduction to Adaptive and Learning Control PDF slides
8.10. Pasi Jylänki Linear Quadratic Regulator PDF
15.10. Jouni Hartikainen Dynamic Programming and HBJ Equation PDF
22.10. Antti Yli-Krekola Stochastic Dynamic Programming and SHJB Equation PDF
29.10. Sami Terho Classical Control PDF
5.11. (no seminar)
12.11. Jarno Vanhatalo Stochastic Linear Quadratic Regulator Problem and the Kalman Filter
19.11. (no seminar)
26.11. (no seminar)
3.12. Sami Terho
Jouni Hartikainen
Reinforcement Learning
Classical Adaptive Control
10.12. Antti Yli-Krekola
Pasi Jylänki
Neural Networks in Control
Adaptive Dual Control

General instructions

In every seminar talk, there is the author who writes a 2-4 page summary paper about the subject and gives the talk, and an opponent, whose task is to make questions and stimulate discussion after the presentation. Every student is the author for (at least) one talk and the opponent for another talk. The author should send the summary paper to the opponent and to the teachers on the thursday preceding the presentation day. The slides should be sent to the teacher lastest on the day preceding the presentation. The opponent prepares at least 2-3 questions about the topic to stimulate discussion after the talk. Normal talk is 30-40 minutes.

Homework exercises

Available here. DL 31.1.2008.

Exercise work

Available here. DL 29.2.2008.

Additional Online Material:


When sending email concerning the course, please add "S-114.4220" or "1144220" to subject.

Dr.Tech. Simo Särkkä

Ph.D. Tuomas Lukka

Tästä sivusta vastaa Sivua on viimeksi päivitetty 03.01.2008