Cybernetics

The course builds on AIS2002 Reguleringsteknikk and AIS2102 Dynamiske systemer, including linear systems theory, classical control systems engineering, and modelling, analysis and control in state space.

Selected topics are announced at the beginning of the semester and will include some of the following:

• Linear quadratic regulator and -estimator
• Optimal state estimation and Kalman filtering
• System identification
• Analysis and control of digital dynamical systems
• Model predictive control
• AI for intelligent control systems, e.g. reinforcement learning
• Possibly other topics

More details on the curriculum will provided during the start of semester.

Knowledge

• The candidate can explain and compare theory, principles, strengths and weaknesses of methods introduced in the course.

Skills

• The candidate can demonstrate use of methods introduced in the course, both through digital tools, simulation, and with physical lab equipment.

General competence

• The candidate can employ digital tools for modelling, analysis, control, simulation, and visualisation of dynamical systems.
• The candidate can explain the value of cybernetics for sustainable processes and systems.
• The candidate can discuss cybernetics in the context of societal opportunities and challenges with respect to innovation, ethics, and sustainability.
• The candidate can present problems, solutions, and results both written and orally in a professional and close-to scientific manner.

Learning activities generally include a mix of lectures, tutorials and practical lab/project work. There will be mandatory works, e.g., assignments or quizzes. A constructivist approach for learning is endorsed, with focus on problem solving and practical application of theory.