| Course Type | Elective Course |
|---|
| Course Level | Master's Degree Without Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 10 |
|---|
| Name of Lecturer(s) |
- |
| Learning Outcomes |
At the end of this course, the students;
- An ability to apply knowledge of mathematics, science, and engineering
- An ability to identify system models
- An ability to identify, formulate, and solve engineering problems
- An understanding of professional and ethical responsibility
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | None |
|---|
| Course Description | Mathematical 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 |
Introduction to System Identification |
|
2nd Week |
Background: Random Variables and Stochastic Processes |
|
3rd Week |
Signals and Systems and Related Topics |
|
4th Week |
Nonparametric Identification |
|
5th Week |
Linear Regression |
|
6th Week |
Input Signals |
|
7th Week |
Parameter Estimation: Minimizing Prediction Error, Identifiability, Consistency, Biase |
|
8th Week |
Least Squares |
|
9th Week |
Parameter Estimation: Convergence and Consistency, Asymptotic Distribution of Parameter Estimates |
|
10th Week |
MIDTERM |
|
11th Week |
Algorithms: Computing the Estimates, Recursive Estimation |
|
12th Week |
Identification in Practice: Aliasing due to Sampling, Closed Loop Data |
|
13th Week |
Bounded but Unknown Disturbances: Identification in the Worst Case, Optimal Algorithms |
|
14th Week |
Bounded but Unknown Disturbances: Optimal Inputs, Robustness Consideration |
|
15th Week |
Adaptive Control: Certainty Equivalence, Stability Issues in Time-varying Systems |
|
16th Week |
Adaptive Control: Stability of an Adaptive Systems |
|
| 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 |
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
35 |
| Assignment |
2 |
10 |
| Project |
2 |
10 |
| Total(%) |
|
45 |
| Contribution of In-term Studies to Overall Grade(%) |
|
45 |
| Contribution of Final Examination to Overall Grade(%) |
|
55 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
3 |
3 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
14 |
4 |
56 |
| Preparation for Final exam |
1 |
60 |
60 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
30 |
30 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
3 |
3 |
| Homework |
2 |
10 |
20 |
| Project |
2 |
40 |
80 |
| Total Work Load | 294 |
| Total Work Load / 30 (h) | 9.8 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
