Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
CONTROL SYSTEMS 200100715371 0 + 0 0 7.0

Prerequisites None

Language of Instruction English
Course Level Graduate Degree
Course Type Compulsory
Mode of delivery
Course Coordinator
Instructors
Assistants
Goals The aim of the Accelerators and Detector Technologies Master of Science Program is to educate the students who have undergraduate education in different departments of fundamental sciences and engineering related about Advanced Technologies, Space, Health, Defense, Nuclear Science, Communication, etc. In research and development activities that can be done by our students through accelerator and detector technologies in sectors, accepted interdisciplinary cooperation, experienced in vacuum, radiation, control systems, skilled in repair and maintenance work, compatible in team work, able to design, operate and manage systems, can use systems in particle accelerators, radiation sources, detector, data analysis systems , researchers, skilled and technical knowledge.
Course Content The Master of Science Program in Accelerator and Detector Technologies is a graduate, Turkish language MSc. program aimed at providing hands-on training on accelerators and related technologies using the Electron Accelerator and Laser Facility infrastructure under the Department of Accelerating Technologies, which is proposed to open at the Institute of Accelerating Technologies of the University of Ankara. Accelerator Technologies Department and Accelerator and Detector Technologies Program will be the first program and discipline to train students on accelerators in our country.
Learning Outcomes 1) Make simulation on accelerators and interpret the results.
2) Links between accelerators with different areas of technology.
3) Software and hardware development applications on accelerator and its components

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Introduction to Control Systems Lecture; Question Answer
Brainstorming
Project Based Learning 		Presentation (Including Preparation Time)
2. Week Architecture of Control Systems Lecture; Question Answer
Brainstorming
Project Based Learning 		Presentation (Including Preparation Time)
3. Week Architecture of Control Systems Lecture; Question Answer
Brainstorming
Project Based Learning 		Presentation (Including Preparation Time)
4. Week Network Lecture; Question Answer

Project Based Learning 		Presentation (Including Preparation Time)
5. Week Control Softwares Lecture; Question Answer
Colloquium
Project Based Learning 		Presentation (Including Preparation Time)
6. Week Operating Systems Lecture; Question Answer
Brainstorming
Project Based Learning 		Presentation (Including Preparation Time)
7. Week Midterm Lecture; Question Answer
Brainstorming
Problem Based Learning 		Presentation (Including Preparation Time)
8. Week Timing Systems Lecture; Question Answer

Problem Based Learning 		Presentation (Including Preparation Time)
9. Week Trajectory Tracking Control Lecture; Question Answer
Brainstorming
Project Based Learning 		Presentation (Including Preparation Time)
10. Week Feedback Systems Lecture; Question Answer
Colloquium
Project Based Learning 		Presentation (Including Preparation Time)
11. Week Feedback Systems Lecture; Question Answer
Brainstorming
Project Based Learning 		Presentation (Including Preparation Time)
12. Week Front-end-Systems Lecture; Question Answer
Brainstorming
Project Based Learning 		Presentation (Including Preparation Time)
13. Week Diagnostics Lecture; Question Answer
Symposium
Project Based Learning 		Presentation (Including Preparation Time)
14. Week Interlock Lecture; Question Answer
Colloquium
Project Based Learning 		Presentation (Including Preparation Time)

Sources Used in This Course
Recommended Sources
Christoph Steier, James Safranek and Xiaobiao Huang, Beam-Based Diagnostics, course material at USPAS

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 14 3
Work Hour outside Classroom (Preparation, strengthening) 14 5
Homework 3 5
Presentation (Including Preparation Time) 1 20
Report (Including Preparation and presentation Time) 1 15
Midterm Exam 1 2
Time to prepare for Midterm Exam 1 15
Final Exam 1 15
Time to prepare for Final Exam 1 15
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
Quick Access Hızlı Erişim Genişlet
Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • ECTS credits and course workload