System Identification and Diagnosis

2018/2019

Prerequisite/Recommended prerequisite for participation in the module

Numerical methods, control theory, probability, statistics and stochastic processes, state-space methods.

Content, progress and pedagogy of the module

Content

System Identification

  • General introduction to modelling and system identification
    • Typical modeling methods: physics-based and experiment-based
    • Parametric and non-parametric models
    • General procedures of system identification
  • Non-recursive methods
    • Least-Square method and its variants
    • Instrumental variable methods
    • Prediction error methods
  • Recursive methods
    • Recursive Least-Square methods
    • Recursive instrumental variable methods
    • Recursive prediction error methods
    • Forgetting factor techniques and time-varying systems identification
  • Introduction to subspace methods
  • MIMO system identification
  • Practical considerations
    • Input signals and persistent excitation
    • Model structure selection
    • Model validation
  • Commercial software and examples

Fault Detection and Diagnosis

  • Fundamental concepts, terms and principles of FDD
    • Terminology
    • Fundamental principles
    • General overview of typical methods
  • FDD modelling and analysis
    • Fault types and classification
    • Fault modelling
    • Fault delectability
    • Fault diagnosability
  • Parameter identification based diagnosis methods
  • State estimation based diagnosis methods

Learning objectives

Knowledge

  • Have comprehension of the fundamental principles of typical methods of system identification
  • Have comprehension of the fundamental concepts, terms and methodologies of abnormal diagnosis
  • Have comprehension of some typical model-based and signal-based diagnosis

Skills

  • Be able to apply the learned knowledge to handle some simple system identification problems under assistance of a commercial software
  • Be able to apply and analyze different diagnosis methods

Competences

  • Independently be able to define and analyze scientific problems within the area of system identification and diagnosis.
  • Independently be able to be a part of professional and interdisciplinary development work within the area of system identification and diagnosis.

Type of instruction

The program is based on a combination of academic, problem-oriented and interdisciplinary approaches and organized based on the following work and evaluation methods that combine skills and reflection: • Lectures • Classroom instruction • Project work • Workshops • Exercises (individually and in groups) • Teacher feedback • Reflection • Portfolio work

Extent and expected workload

Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student

Exam

Exams

Name of examSystem Identification and Diagnosis
Type of exam
Written or oral examination
ECTS5
Permitted aids
With certain aids, see list below
Unless otherwise stated in the course description in Moodle, it is permitted to bring all kinds of (engineering) aids including books, notes and advanced calculators. If the student brings a computer, it is not permitted to have access to the Internet and the teaching materials from Moodle must therefore be down loaded in advance on the computer. It is emphasized that no form of electronic communication must take place.
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentAs stated in the Joint Programme Regulations.
http:/​/​www.engineering.aau.dk/​uddannelse/​studieadministration/​

Facts about the module

Danish titleSystemidentifikation og diagnosticering
Module codeEN-IRS1-3
Module typeCourse
Duration1 semester
SemesterAutumn
ECTS5
Empty-place SchemeYes
Location of the lectureCampus Esbjerg
Responsible for the module

Organisation

Study BoardStudy Board of Energy
FacultyFaculty of Engineering and Science