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 2023-2024. 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

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

Coursework requirements

Exercises
At least 6 of 8 exercises should be approved by course instructor within the specified deadlines to get access to 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

Course assessment

There must be an early dialogue between the course coordinator, the student 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 course 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