Information Package

Program of Artificial Intelligence Engineering (English)

AI425

SYSTEM IDENTIFICATION

Course Code
AI425
Semester
-
Theory+Practice
3 + 0
ECTS
5
Course TypeElective Course
Course LevelBachelor's Degree
Year of Study-
Semester-
ECTS5
Name of Lecturer(s) -
Learning Outcomes

At the end of this course, the students;

  1. To be able to make modeling of systems under the influence of nonlinear distorting factors.
  2. To understand the models of linear time-invariant systems.
  3. Estimation of known and unknown noise model.
  4. Having knowledge of modeling of time varying and nonlinear systems.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme Components
Course DescriptionMathematical models of systems from observations of their behavior; time series, state-space, and input-output models; model structures, parameterization, and identifiability; non-parametric methods; prediction error methods for parameter estimation, convergence, consistency, and asymptotic distribution; relations to maximum likelihood estimation; recursive estimation; relation to Kalman filters; structure determination; order estimation; Akaike criterion; bounded but unknown noise model; and robustness and practical issues.
Course Contents
WEEK TOPICS
1st Week Systems and Models, Modeling Concept, Model Types and Examples, Mathematical Modeling and System Identification.
2nd Week Flow chart of system recognition, basic definitions and concepts.
3rd Week Nonparametric methods in system identification.
4th Week Transition function, frequency response methods.
5th Week Frequency Response Methods of Nonlinear Disruptions.
6th Week Frequency Response Methods of Nonlinear Disruptions.
7th Week The Concept of Continuous Warning, Constant Warning Signs.
8th Week MIDTERM
9th Week Model Constitution of Linear Time Invariant Systems.
10th Week Estimation of Known Noise Model.
11th Week Estimation of Known Noise Model.
12th Week Estimation of Unknown Noise Model.
13th Week Model Structure Selection and Verification.
14th Week Model Structure Selection and Verification.
Recommended or Required Reading* Ljung, Lennart. System Identification: A Theory for the User. 2nd ed. Upper Saddle River, NJ: Prentice Hall, 1998. ISBN: 0136566952
Planned Learning Activities and Teaching Methods
  • Lecture
  • Questions/Answers
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 35
Project 1 20
Total(%) 55
Contribution of In-term Studies to Overall Grade(%) 55
Contribution of Final Examination to Overall Grade(%) 45
Total(%) 100
Language of Instruction-
Work Placement(s)No
LO1 LO2 LO3 LO4
K1
K2
K3
K4
K5
K6
K7
K8
K9
K10
K11
K12