Control Engineering 2

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. 

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. 

Lectures and exercises.