| Course Type | Elective Course |
|---|
| Course Level | Master's Degree With 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 design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
- 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 | Description of optimization, Calculation of extremes and parameter optimization, Lagrange multipliers. Manner criteria, Dynamic programming, Calculation of variations calculation and Pontryagin's minimum principle, Dynamic optimization in the face of equivalence and inequality, Hamilton-Jacobi-Bellmann equation, Matrice Riccati equation, optimization of discrete time control systems, Numerical solution methods of optimal control problems. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Description of optimization |
|
2nd Week |
Calculation of extremes and parameter optimization |
|
3rd Week |
Lagrange multipliers |
|
4th Week |
Manner criteria, Dynamic programing |
|
5th Week |
Calculation of variations and Pontryagin's minimum principle |
|
6th Week |
Dynamic optimization in the face of equivalence and inequality |
|
7th Week |
Hamilton-Jacobi-Bellmann equation |
|
8th Week |
MID TERM |
|
9th Week |
Matrice Riccati equation |
|
10th Week |
Matrice Riccati equation |
|
11th Week |
Optimization of discrete time control systems |
|
12th Week |
Optimization of discrete time control systems |
|
13th Week |
Numerical solution methods of optimal control problems |
|
14th Week |
Numerical solution methods of optimal control problems. |
|
| Recommended or Required Reading | Global Methods in Optimal Control Theory, Krotov, Vadim F., Marcel Dekker, Inc., Newyork |
|---|
| Planned Learning Activities and Teaching Methods |
- Questions/Answers
- Lecture
- Problem Solving
- Practice
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
35 |
| Assignment |
4 |
15 |
| Project |
1 |
5 |
| Total(%) |
|
55 |
| Contribution of In-term Studies to Overall Grade(%) |
|
55 |
| Contribution of Final Examination to Overall Grade(%) |
|
45 |
| 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 |
40 |
40 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
25 |
25 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
3 |
3 |
| Homework |
4 |
15 |
60 |
| Presentation (including preperation) |
1 |
2 |
2 |
| Project |
1 |
70 |
70 |
| Total Work Load | 301 |
| Total Work Load / 30 (h) | 10.03 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
