Course Objectives

Gain knowledge of control methods, control structures and practical modelling. Be able to carry out elementary system identification and modelling of selected physical systems.

Course Description

Control structures in addition to the normal PID control: parameter-constrained control, forward coupling, multivariable control, downtime compensation and the principles for estimation of condition. Simple nonlinear control based on de-coupling by amongst other things nonlinear feedback. Discrete control and modelling as well as simulation of selected industrial models.

Automation techniques for identifying physical processes and systems to achieve simple models from logged raw data will be presented.

Automation structures and systems for management of important process variables such as temperature, pressure and motion, and for connected processes. Introduction to, amongst other things, fuzzy systems, expert systems mhp robust control, as well as new trends in the development of automated systems.

Learning Methods

Lectures, calculations and project.

Assessment Methods

Written final examination (70%). A number of exercises are obligatory which counts 30% of the final degree.

Students must achieve passing marks in all of the examinations, and the final assessment will consist of a single grade based on the marks from the aforementioned examinations.

Minor adjustments may occur during the academic year, subject to the decision of the Dean