Course content

The course contains a selection of the following topics, with an emphasis on practical use of digital tools: 

• Modelling and simulation of dynamical systems/processes; 
• State space models, state space analysis, and conversion to transfer functions; 
• System identification and model fitting; 
• Methods for designing, tuning and analyzing controllers;
• Design of control-relevant filters and lead-lad elements;
• Alternative control structures such as feed-forward, cascade, and ratio control; 
• Solutions related to certain practical challenges in control systems;
• Nonlinear systems, linearization, and gain scheduling;
• Methods for analysis and control of multivariable systems;
• Observers and state estimation.
• Other topics are possible. 

Learning outcome

Knowledge: The candidate can explain  

• the need for and the basic functionality of modern ODE solvers; 
• how simple state estimators work;
• control structures such as feed-forward, cascade, and ratio control;  
• challenges and solutions associated with multivariable control systems. 

Skills: The candidate can  

• perform mathematical modeling of dynamical systems; 

• implement solutions to common practical challenges occurring in control systems;
• use modern computer tools for simulation, control and analysis of dynamical systems; 
• design, adjust and analyze controllers and filters in both the time and Laplace domain;
• identify and fit simple process models from data; 
• analyze simple multivariable control systems.  

General competence: The candidate understands the strengths and limitations of theoretical studies in relation to experimental work, in addition to having a basis for further specialization in advanced control engineering methods. 

Digitalization: The course contributes by enabling the candidate to use modern computer tools as an aid in all mentioned skill moments. 

Learning methods and activities

Lectures and exercises.

Compulsory assignments

• Assignments and lab

Specific conditions

Recommended previous knowledge

IFYKJT1001 - Physics/Chemistry, AIST1001 - Automation, introduction and IELEx2002 - Control Engineering or similar.

Required previous knowledge

For applications for credentials, approval and incorporating of courses from previous semesters or other institutions' corresponding education programs, each application will be processed individually and the applicant should expect credit reductions for overlapping courses.

Course materials

Lecture notes. Exercises with solutions. Textbooks specified at the start of the semester.

Credit reductions