ECTS - Estimation and Identification for Engineering Systems
Estimation and Identification for Engineering Systems (MDES630) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Estimation and Identification for Engineering Systems | MDES630 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| Course Objectives | At the end of the course students will gain the ability to design filters for state estimation and will experience the implementation of the designed filters on physical systems. Also, some techniques in system identification will be discussed and students will practice experiments for system identification. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Kalman filtering, nonparametric identification techniques and parameter estimation methods; implementation of filtering algorithms on physical systems and collecting data from real systems. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | State estimation, review of observers | - |
| 2 | Kalman filter | - |
| 3 | Extended Kalman filter | - |
| 4 | Unscented Kalman filter | - |
| 5 | Unscented Kalman filter | - |
| 6 | Case studies | - |
| 7 | Case studies | - |
| 8 | Concepts in system identification | - |
| 9 | Nonparametic methods, parameter estimation methods | - |
| 10 | Least squares estimation | - |
| 11 | Maximum likelihood estimation | - |
| 12 | Prediction error method | - |
| 13 | Neural networks for identification | - |
| 14 | Case studies | - |
| 15 | Overall review | - |
| 16 | Final exam | - |
Sources
| Course Book | 1. Kumar, P. R., Varaiya, P., Stochastic Systems: Estimation, Identification, and Adaptive Control, Prentice Hall, 1986. |
|---|---|
| Other Sources | 2. Ljung, L., System Identification, Theory for the User, PTR Prentice Hall, New Jersey, 1987. |
| 3. Maybeck, P. S., Stochastic Models, Estimation, and Control, Academic Press, 1979. | |
| 4. Minkler G., Minkler J. Theory and Application of Kalman Filtering, Magellan Book Company, USA, 1993. | |
| 5. Nelles O., Nonlinear System Identification from Classical Approaches to Neural Networks and Fuzzy Models, Springer, 2001 |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | 2 | 40 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 40 |
| Final Exam/Final Jury | 1 | 20 |
| Toplam | 5 | 100 |
| Percentage of Semester Work | 80 |
|---|---|
| Percentage of Final Work | 20 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Ability to carry out advanced research activities, both individual and as a member of a team | |||||
| 2 | Ability to evaluate research topics and comment with scientific reasoning | |||||
| 3 | Ability to initiate and create new methodologies, implement them on novel research areas and topics | |||||
| 4 | Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions | |||||
| 5 | Ability to apply scientific philosophy on analysis, modelling and design of engineering systems | |||||
| 6 | Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level | |||||
| 7 | Contribute scientific and technological advancements on engineering domain of his/her interest area | |||||
| 8 | Contribute industrial and scientific advancements to improve the society through research activities | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 2 | 32 |
| Presentation/Seminar Prepration | |||
| Project | 3 | 10 | 30 |
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 8 | 16 |
| Prepration of Final Exams/Final Jury | 1 | 10 | 10 |
| Total Workload | 136 | ||