Cybernetics

The course contains the following main topics:
Linear systems theory and classical control theory (review).
Modelling, analysis, and control design in state space.
Quadratic optimal control and -estimation (continuous Kalman filter).

Other topics may be included, e.g., analysis and control design of digital systems, discrete-time Kalman filter, model predictive control (MPC), or genetic algorithms for parameter optimisation.

Learning outcomes - Knowledge:

* explain strengths and weaknesses of using linearised models.

* describe and compare classical and modern control engineering approaches.

Learning outcomes - Skills:

* analyse stability and performance of linear, time-invariant, continuous-time, and digital systems.

* determine controllability and observability and design state feedback controllers and -estimators based on pole placement or quadratic optimisation for continuous-time and digital systems.

* use advanced methods for optimal and robust control design, for example model predictive control (MPC), or other metods.

Learning outcomes - Competence:

* use computers and software tools (Matlab/Simulink) for simulations (modelling, analysis, control) and visualisation of the dynamics of systems.

* present problems, solutions, and results in a professional and near-scientific manner, both written and orally.

Pedagogical methods:

This course uses the following pedagogical methods:

* Workshops consisting of lectures, problemsolving in groups or independently, practical demonstrations, case studies, presentations and discussion, with a focus on simulation, practical applications, and research-based and constructive learning.

* Compulsory bi-weekly labs with assignments collected in portfolio for submission.

* Compulsory mid-semester test.

The labs and mid-semester test must be passed for admission to the exam. This motivates students to work steadily towards subgoals from day one. Feedback from the labs and the mid-semester test provide an opportunity to adjust course both for the teacher and for the students before it is too late.


Admission to the exam:

* Lab portfolios documenting the bi-weekly compulsory lab assignments must be submitted and passed for admission to the exam.

* A mid-semester test must be passed for admission to the exam.

The course has course material in English. The teaching is conducted in Norwegian if there are no foreign students in the class