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Measurement and feedback control 7.5 credits

Mät- och reglerteknik
First cycle, R0005E
Course syllabus valid: Autumn 2019 Sp 1 - 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.

Syllabus established
by Jonny Johansson, HUL SRT 15 Feb 2018

Last revised
by Jonny Johansson, HUL SRT 15 Feb 2019

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

Entry requirements

In order to meet the general entry requirements for first cycle studies you must have successfully completed upper secondary education and documented skills in English language and Basic knowledge of the Laplace transform, e.g. from the course M0018M Linear Analysis or M0046M Mathematics Space. Alternative to completed courses can be corresponding knowledge acquired through work within the process industry or electronics sector.

More information about English language requirements


The selection is based on 1-165 credits.

Course Aim

The course aim is for students to acquire basic knowledge of feedback systems, their design and their use in control engineering applications.

The students should have the skills and knowledge to:

  • demonstrate knowledge of basic methods and terminology of measurement and instrumentation system.
  • demonstrate basic knowledge of proven methods for the design of measurement systems.
  • demonstrate knowledge of basic methods and terminology of automatic control.
  • demonstrate a basic knowledge of proven methods for designing controllers.
  • demonstrate the ability to model and simulate dynamic systems.
  • using mathematical methods to analyze the static, dynamic and frequency characteristics of dynamic systems.
  • use standard methods for designing and analyzing controllers.
  • demonstrate an ability to, in a team, design and implement controllers, as well as evaluate their performance for a real process.
  • demonstrate the ability to, both orally and in writing, report on the practical work of modeling, design and implementation of closed loop control for a real process.
  • identify the usefulness of basic control methods and their limitations, and identify the need for more advanced methods.


Automatic Control is the science of controlling processes. A typical example is the cruise control in a car (In this case the car is the "process") that by varying the throttle ("input" to the process) will keep the speed ("output" of the process) constant despite hills and wind (so-called "disturbances"). Other common examples include companies in the process industry, where the aim is to control pressures and temperatures, and in communication where you want to control data rates and transmission powers.

Automatic Control is not limited to technical processes but can also be applied in areas such as economics and medicine. One example is the human body's, highly sophisticated control system that is able to keep the body temperature constant at 37 degrees Celsius despite variations in ambient temperature or to keep the body weight constant despite assiduous efforts to better nutrition and exercise.

This course is our first course in control theory and covers the classical methods of analysis and synthesis of feedback control for a wide range of technical processes. This course provides in-depth knowledge of the subject, sufficient for non-specialists in control theory to develop simple control systems. The is a necessary basis for continued studies in the subject.

During the course, the following methods and concepts will be discussed:

Introduction: Introduction to general control engineering concepts, such as static systems, dynamic systems, process, reference signal (setpoint), control signal, output signal, noise, open systems, measurement signal, the feedback, controller.

Dynamic models: Mathematical modeling of physical systems. Differential equations. Differential equations in state space. Linearization.

Simulation: Introduction to simulation of dynamic systems and the programs Regsim and Simulink.

Mathematical tools: Laplace transform and its properties. Transfer function. Static gain. Super-position principle. Block Diagrams. Specifications. Rise time. Settling time. Overshoot. Poles and Zeroes. Modeling based on emperical data.

Feedback systems: PID controller. Process disturbances. Steady state control error. Ziegler-Nichols methods. Lambda tuning. Stability Concepts.

Frequency domain: The frequency function. Frequency analysis. Bode plots. Asymptotic Bode plot. Stability. Stability Margins. Compensation. Sensitivity. Time delays.

Digital control: Approximation of continuous controllers. Sampling.


Course activities are lectures, laboratory sessions and problem solving sessions. The laboratory sessions are designed to provide insight into how the theory can be applied in practical control engineering work, which also results in increased familiarity with analytical and simulation tools.

The laboratory work makes use of a water tank process where students, in groups, will produce a level control system.

Written exam with differentiated grades and graded laboratory work .

Wolfgang Birk

Literature. Valid from Autumn 2018 Sp 1 (May change until 10 weeks before course start)
Gene F. Franklin, Feedback Control of Dynamic Systems, Global Edition, Upplaga 7, Pearson Education Limited, ISBN 9781292068909.

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

CodeDescriptionGrade scaleHPStatusFrom periodTitle
0003Laboratory workU G#2.00MandatoryA19
0004Problem solvingU G#2.00MandatoryA19
0005Written examG U 3 4 53.50MandatoryA19

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.