• Basic information
• Learning outcomes
• Contents
• Assessment
• Workload

Learning outcomes

Upon successful completion of this course, students will be able to:

1. Model mechanical and electrical systems as feedback control structures in frequency and time domain.

   Contribution to Program Outcomes

   1. Adequate knowledge of mathematics, science and mechanical engineering disciplines; ability to use theoretical and applied knowledge in these fields in solving complex engineering problems.
   2. Ability to identify, formulate and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.
   3. Ability to work effectively in disciplinary and multi-disciplinary teams; individual working skills.

   Method of assessment

   1. Written exam
   2. Homework assignment
   3. Term paper
2. Evaluate time and frequency domain responses of the control system, and assess the performance in terms of transient response, steady-state error, and stability.

   Contribution to Program Outcomes

   1. Adequate knowledge of mathematics, science and mechanical engineering disciplines; ability to use theoretical and applied knowledge in these fields in solving complex engineering problems.
   2. Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively.
   3. Being familiar with multivariate mathematics and differential equations, statistics and optimization, using this knowledge to develop models describing problems in mechanical engineering mathematically; be able to solve mechanical engineering problems using computer programming and computational methods; ability to use design and analysis programs related to mechanical engineering.

   Method of assessment

   1. Written exam
   2. Homework assignment
   3. Term paper
3. Becomes familiar with design model-based controllers for specific requirements of the mechanical and electrical systems.

   Contribution to Program Outcomes

   1. Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose.
   2. Being familiar with multivariate mathematics and differential equations, statistics and optimization, using this knowledge to develop models describing problems in mechanical engineering mathematically; be able to solve mechanical engineering problems using computer programming and computational methods; ability to use design and analysis programs related to mechanical engineering.
   3. The ability to work professionally by preparing and managing projects in the fields of mechanical, thermal systems or automatic control.

   Method of assessment

   1. Written exam
   2. Homework assignment
   3. Term paper
4. Becomes aware of developments in control systems theory by learing to access and study worldwide information in this area.

   Contribution to Program Outcomes

   1. Ability to communicate effectively orally and in writing; knowledge of at least one foreign language; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
   2. Awareness of the necessity of lifelong learning; the ability to access information, follow developments in science and technology, and constantly renew oneself.

   Method of assessment

   1. Homework assignment
   2. Term paper

Contents
Week 1:	Introduction to control systems and feedback; basic examples.
Week 2:	Modeling of mechanical and electrical systems; transfer functions.
Week 3:	Modeling of mechanical, electrical, and electromechanical systems; block diagrams.
Week 4:	Time-domain analysis; state-space models; step/impulse responses.
Week 5:	Transient response of 1st, 2nd, and higher-order systems.
Week 6:	Stability via Routh-Hurwitz; steady-state error and system type.
Week 7:	Root locus method; gain effects on poles and behavior.
Week 8:	Gain tuning via root locus. Midterm Exam covering topics from Week 1 to Week 6.
Week 9:	Compensator design using root locus.
Week 10:	Bode and Nyquist diagrams; frequency response.
Week 11:	Special design topics and examples via root locus.
Week 12:	Design using frequency response; gain/phase margins.
Week 13:	Programming applications in control systems.
Week 14:	Problem solving; project discussions and feedback.
Week 15*:	Comprehensive review
Week 16*:	Final exam (min. 25 required)
Textbooks and materials:	Nise, Norman S. Control systems engineering. John Wiley Sons, 2020. Dorf, Richard C., Bishop, Robert H. Modern Control Systems: Pearson New International Edition: Introduction to Total Quality. Taiwan: Pearson Education Limited, 2014. Ogata, Katsuhiko. Modern Control Engineering. United Kingdom: Prentice Hall, 2010.
Recommended readings:	D. Xue, Y. Chen, D. P. Atherton, Linear feedback control : analysis and design with MATLAB, SIAM, 2007. J Van de Vegte, Feedback Control System, Prentice Hall, 1994.
	* Between 15th and 16th weeks is there a free week for students to prepare for final exam.

Assessment
Method of assessment	Week number	Weight (%)
Mid-terms:	8	20
Other in-term studies:		0
Project:	14	40
Homework:		0
Quiz:	1-14	10
Final exam:	16	30
	Total weight:	(%)

Workload
Activity	Duration (Hours per week)	Total number of weeks	Total hours in term
Courses (Face-to-face teaching):	3	14
Own studies outside class:	3	14
Practice, Recitation:	0	0
Homework:	0	0
Term project:	3	2
Term project presentation:	0	0
Quiz:	5	4
Own study for mid-term exam:	4	1
Mid-term:	3	1
Personal studies for final exam:	5	1
Final exam:	3	1
		Total workload:
		Total ECTS credits:	*
	* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)