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 | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| Consent of the instructor |
| Course Language | English |
|---|---|
| Course Type | N/A |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
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| 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;
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| 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 expand and get in-depth information with scientific researches in the field of mechanical engineering, evaluate information, review and implement. | |||||
| 2 | Have comprehensive knowledge about current techniques and methods and their limitations in Mechanical engineering. | |||||
| 3 | To complete and apply knowledge by using scientific methods using uncertain, limited or incomplete data; use information from different disciplines. | |||||
| 4 | Being aware of the new and developing practices of Mechanical Engineering and being able to examine and learn when needed. | |||||
| 5 | Ability to define and formulate problems related to Mechanical Engineering and develop methods for solving and apply innovative methods in solutions. | |||||
| 6 | Ability to develop new and/or original ideas and methods; design complex systems or processes and develop innovative/alternative solutions in the designs. | |||||
| 7 | Ability to design and apply theoretical, experimental and modeling based researches; analyze and solve complex problems encountered in this process. | |||||
| 8 | Work effectively in disciplinary and multi-disciplinary teams, lead leadership in such teams and develop solution approaches in complex situations; work independently and take responsibility. | |||||
| 9 | To establish oral and written communication by using a foreign language at least at the level of European Language Portfolio B2 General Level. | |||||
| 10 | Ability to convey the process and results of their studies systematically and clearly in written and oral form in national and international environments. | |||||
| 11 | To know the social, environmental, health, security, law dimensions, project management and business life applications of engineering applications and to be aware of the constraints of their engineering applications. | |||||
| 12 | Ability to observe social, scientific and ethical values in the stages of data collection, interpretation and announcement and in all professional 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 | ||