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Advanced Control Design 7.5 credits

Avancerade reglersystem
Second cycle, R7014E
Course syllabus valid: Spring 2022 Sp 3 - Present
The version indicates the term and period for which this course syllabus is valid. The most recent version of the course syllabus is shown first.

Education level
Second cycle
Grade scale
G U 3 4 5
Control Engineering
Subject group (SCB)
Automation Technology
Main field of study
Engineering Physics and Electrical Engineering

Entry requirements

Knowledge in the subject of Automatic control, specifically regarding frequency response, state-space form, and state feedback. Experience with using Matlab/Simulink or similar for analysis of control systems is also presumed. These prerequisites correspond to the course R7003E Automatic control. Good knowledge in English equivalent to English 6.

More information about English language requirements


The selection is based on 20-285 credits

Course Aim

After completion of the course the student shall be able to

-       show a deep knowledge of control engineering methods and terminology for robust and optimal control;

-       show deep understanding of mathematical methods to design advanced control schemes for dynamic system which can be non-linear, uncertain and multivariable;

-       demonstrate the ability to model non-linear and multivariable dynamic systems based on empirical data and formulate descriptions of uncertainties and disturbances in 
        dynamical systems;

-       demonstrate an ability to formulate performance requirements for control systems and determine what performance is achievable;

-       use standard methods for designing and analyzing robust, optimal and predictive controllers, even in the multivariable case;

-       demonstrate an ability to, in a group, simulate, analyze, evaluate and implement robust, optimal and predictive controllers for a real process and to report on this work,
        both orally and in writing;

-       show the ability to identify constraints of simple controllers and the need for more advanced methods;
-       demonstrate an ability to analyze observability of a dynamic system, to design and implement estimators for states and non-measurable variables


The course deals with design of advanced control systems for real-life engineering systems and the analysis of their performance characteristics. Emphasis is on techniques which render robust and optimal control systems.

When attempting to apply control to a complex real-world process, a number of problems appear that this course provides theoretical methods to handle. Many technical systems, such as industrial processes, robots, vehicles, motors etc. are best described in the form of nonlinear dynamical systems. Methods to analyze these system descriptions are important to be able to e.g. perform measurement and control in these systems.

The first problem treated in the course is the derivation of process models which are non-linear and are never an exact description of the process in question. How to analyze the non-linear system description and also describe model uncertainty is treated, as well as methods for designing robust and optimizing controllers that achieve various criteria, like e.g. stability or optimality, and performance despite variations in the process.

The second problem is that many processes that are interesting to be able to control are in practice multivariable, i.e. that several inputs affect several outputs. Basic notions, such as poles and zeros, controllability and observability are treated for multivariable systems, as well as methods to determine when single input and single output controllers can be used on a multivariable process with acceptable performance. Controllers, based on optimization of a cost function, are treated for the situation where multivariable control must be used.

The third problem is estimation of either not directly measurable quantities or that a quantity can not be measured with sufficient quality. For this end, the Kalman filter and the extended Kalman filter are introduced enabling estimation and sensor fusion based on measurements.

The theoretical parts of the course are supplemented with practical lab work in the form of project assignments on an experimental or simulated setup in the laboratory of the Department of Computer Science and Electrical Engineering.

Each course occasion´s language and form is stated and appear on the course page on Luleå University of Technology's website.

The course activities are lectures, laboratory sessions, and problem seminars. Laboratory sessions are performed in groups of no more than three students and accounted for with written reports and a demonstration. During the problem seminars, the students present in groups solutions to exercises that are handed out in advance.

If there is a decision on special educational support, in accordance with the Guideline Student's rights and obligations at Luleå University of Technology, an adapted or alternative form of examination can be provided.

Written exam with differentiated grades and graded laboratory work.

Transition terms
The course can be combined with no more than one of the two courses R7004E och R7005E

Wolfgang Birk

Literature. Valid from Spring 2020 Sp 3 (May change until 10 weeks before course start)
Glad, T. and L. Ljung: Control Theory. Multivariable and Nonlinear Methods. Taylor & Francis.

Course offered by
Department of Computer Science, Electrical and Space Engineering

CodeDescriptionGrade scaleHPStatusFrom periodTitle
0002Laboratory workU G#3.00MandatoryA17
0004Written examG U 3 4 54.50MandatoryS22

Study guidance
Study guidance for the course is to be found in our learning platform Canvas before the course starts. Students applying for single subject courses get more information in the Welcome letter. You will find the learning platform via My LTU.

Syllabus established
by Jonny Johansson, HUL SRT 15 Feb 2017

Last revised
by Jonny Johansson, HUL SRT 17 Feb 2021