Recommended prerequisite for participation in the module

Content, progress and pedagogy of the module

Learning objectives

Knowledge

• Have knowledge and understanding within adaptive control techniques, such as gain scheduling, self-tuning regulators, and model reference adaptive control
• Have knowledge about principles and standard schemes of model predictive control techniques
• Have knowledge about formulating the model predictive control for a given system considering cost functions and constraints

Skills

• Be able to use model-based adaptive control and model predictive control, which can act as efficient control design methods for control systems
• Be able to analyse the dynamic behaviour of an adaptive control and model predictive control system
• Be able to investigate stability of an adaptive or model predictive control system
• Be able to implement model predictive control using relevant optimisation software
• Be able to design and simulate adaptive and predictive controllers and make judgment of the benefits and drawbacks of the used techniques

Competences

• Be equipped with fundamental knowledge and basic skills in the areas of adaptive and predictive control
• Be able to define and analyse scientific problems within the area of adaptive and predictive control
• Be able to select proper adaptive and predictive control methods and apply the selected methods into real-life applications
• Be able to be a part of professional and interdisciplinary development work within the area of adaptive and predictive control

Type of instruction

The course is taught by a mixture of lectures, workshops, exercises, mini-projects or self-studies, including e-learning.

Extent and expected workload

Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student

Exam

Exams