Decision Systems


1. Study and implementation of state-space optimal control techniques together with the design of state observer using the Kalman filter approach;
2. Study of human decision and cognition;
3. Study and implementation of global optimization techniques.

General characterization





Responsible teacher

Bruno João Nogueira Guerreiro


Weekly - 4

Total - 59

Teaching language



Students must have attended the courses Control Theory and Computer Control.



Class slides, Bruno Guerreiro, 2019.

Optimal Control, Lewis & V. Syrmos, 1995. 

Polynomial optimal control, Paulo Gil, UNL, 2017 (PT).

Discrete Kalman Filter, Paulo Gil, UNL, 2002 (PT).

Discrete optimal control  Paulo Gil, UNL, 2002 (PT).



Exercises on optimal control, Paulo Gil, 2018.

Problems on evolutionary computation, Paulo Gil e Fábio Januário, 2018.

Enunciados dos trabalhos de laboratório, Bruno Guerreiro, 2019.

 Adaptive Control, Astrom & Wittenmark, Addison Wesley, 1995

System Identification, L. Ljung, Prentice-Hall, 1999

MATLAB Primer:

Simulink User Guide:

Teaching method

The course is organized in theoretical-practical classes and laboratory classes. In the theoretical-practical classes the concepts are introduced and applied in concrete cases from an analytical point of view. In addition, the practical (or laboratory) classes are directed to the development of the techniques addressed in the theoretical classes applied to concrete cases, with the goal to obtain experimental results and their analysis.

Small quizzes will be given during the theoretical-practical classes, usually focusing on concepts already addressed and that students should have consolidated in self-study. However, bridging the gap between traditional teaching methods and the flipped class-room method, some of these questionnaires will address topics not yet addressed during classes, so that students are motivated to prepare the introduction of new themes.

Evaluation method

The final grade (FG) is defined as: FG = 0.5*T + 0.1*Q+ 0,4*P

- Teoretical component (T): maximum between the average of the 2 tests and the exam;

- Short-quizzes component (Q): to promote self-study during the semester, short quizzes will be given for either in class or as homework about the theoretical contents, where the grade of this component is the average of these quizzes;

- Practical component (P): average of practical works (minimum average of 10/20).

Subject matter

Part I:
1. Optimal control for discrete-time polynomial systems
2. Discrete-time Kalman filter
3. Optimal control for discrete-time state-space systems

Part II:
4. Human-in-the-loop control
5. Global optimization techniques


Programs where the course is taught: