Cybernetics (ELE620)

Continuous-time and discrete-time systems theory, using both the state-space representation and transfer functions. Discretization of continuous-time systems. Stability, controllability and observability. State-feedback and LQR control. State observation and Kalman filter. Parametrical system identification: ARX and ARMAX models, recursive least-squares approaches. Introduction to model-based fault diagnosis.


Course description for study year 2024-2025. Please note that changes may occur.

Facts

Course code

ELE620

Version

1

Credits (ECTS)

10

Semester tution start

Autumn

Number of semesters

1

Exam semester

Autumn

Language of instruction

English

Offered by
Time table

View course schedule

Content

NB! This is an elective course and may be cancelled if fewer than 10 students are enrolled by August 20th for the autumn semester.

Continuous-time and discrete-time systems theory, using both the state-space representation and transfer functions. Discretization of continuous-time systems. Stability, controllability and observability. State-feedback and LQR control. State observation and Kalman filter. Parametrical system identification: ARX and ARMAX models, recursive least-squares approaches. Introduction to model-based fault diagnosis.

Learning outcome

  • Describe discrete and continuous dynamic systems by transfer-functions and state-space-models
  • Transform a dynamic system from one form to another
  • Use state-space models for control purposes
  • Do state and parameter estimation using state observers, Kalman filtering and RLS
  • Do fault diagnosis using model-based approaches

Required prerequisite knowledge

None

Exam

Form of assessment Weight Duration Marks Aid
Written exam 1/1 4 Hours Letter grades No printed or written materials are allowed. Approved basic calculator allowed

Digital exam

Coursework requirements

Exercises
7 assignments should be delivered within the specified deadlines. Each delivery will be graded between 0 and 100 points. 420 points are required to get access to the exam.

Course teacher(s)

Course coordinator:

Damiano Rotondo

Course teacher:

Damiano Rotondo

Laboratory Engineer:

Didrik Efjestad Fjereide

Head of Department:

Tom Ryen

Method of work

6-8 hours of lectures per week.

Overlapping courses

Course Reduction (SP)
System identification (MIK130_1) 10
System identification (MIK130_2) 10

Open for

Admission to Single Courses at the Faculty of Science and Technology
Robot Technology and Signal Processing - Master of Science Degree Programme
Exchange programme at Faculty of Science and Technology

Course assessment

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital subject evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.

Literature

The syllabus can be found in Leganto