Electrical and Electronics Engineering
Course Details
KTO KARATAY UNIVERSITY
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Electrical and Electronics Engineering
Course Details
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Electrical and Electronics Engineering
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 05141408 | Mechatronics | 2 | Spring | 4 | 3+0+0 | 5 | 5 |
| Course Type | Elective |
| Course Cycle | Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | Asst. Prof. Hüseyin Oktay Altun |
| Instructor(s) | - |
| Instructor Assistant(s) | - |
Course Content
The available models of the basic principles of intelligent systems, Complex engineering systems, control and recognition. Intelligent control approaches. Possible technologies: easy calculation (Soft computing), conventional methods and information theory; data management applications, sensor fusion, control systems, diagnosis / prediction systems, fault-tolerant control and supervised control. Application fields: textile and fiber processing, pulp and paper, aerospace and automotive systems, etc. Artificial Neural Networks (ANN), Fuzzy Logic (FL), Genetic Algorithms (GA). The use of ANN, FL and GA in control, estimation, planning, diagnosis, imaging, and heuristic search methods.
Objectives of the Course
This course aims to the students to use and develop intelligent mechatronics systems.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | |
| Support Courses | |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Introduction |
| 2 | Mechatronics and intelligent systems |
| 3 | Complex engineering systems, control and recognition |
| 4 | Intelligent control approaches |
| 5 | Possible technologies: easy calculation (Soft computing), conventional methods and information theory data management applications |
| 6 | Possible technologies: easy calculation (Soft computing), conventional methods and information theory data management applications |
| 7 | Sensor fusion, control systems, diagnosis / prediction systems, fault-tolerant control and supervised control. |
| 8 | Sensor fusion, control systems, diagnosis / prediction systems, fault-tolerant control and supervised control. |
| 9 | Artificial intelligence |
| 10 | Artificial intelligence |
| 11 | Neural Networks and fuzzy systems |
| 12 | Genetic Algorithms (GA). The use of ANN, FL and GA in control |
| 13 | Estimation, planning, diagnosis, imaging, and heuristic search methods. |
| 14 | Application fields: textile and fiber processing, pulp and paper, aerospace and automotive systems |
Textbook or Material
| Resources | D.A. Bradley, D. Dawson, D. Seward, S. Burge "Mechatronics and the Design of Intelligent Machines and Systems", CRC Press Inc (2000) |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Quiz | - | - |
| Listening | - | - |
| Midterms | - | - |
| Final Exam | - | - |
| Total | 0 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 0 | 0 | 0 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 0 | 0 | 0 |
| Midterms | 0 | 0 | 0 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 0 | 0 | 0 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 0 | ||
| Total Work Load / 30 | 0 | ||
| Course ECTS Credits: | 0 | ||