Mathematical methods in Electrical Engineering and Automation Technology (15 ECTS)

Learning outcomes

After completion of the course the student has more profound knowledge of advanced mathematical aspects of electrical engineering and automation technology. He/she is able to use differential and integral calculus in solving problems in these fields. He/she is able to use Matlab software in analyzing related complex mathematical problems.

Content

1. Differential and integral calculus of functions of several variables
• partial derivatives
• double and triple integrals
• line integrals
• Stokes, Green and divergence theorems
• applications in electrical engineering
• Matlab exercises

2. Control engineering and applied mathematics
• control and system theory and applications
• ordinary differential equations in control engineering
• Laplace transform
• Matrices and matrix algebra
• dynamic systems
• transfer functions and frequency domain models
• PID-controller
• design and analysis of controllers
• simulation of a dynamic system with feedback
• Matlab exercises

3. Integral transforms and signal theory
• signals and systems in time domain
• convolution integral
• Fourier series of periodical signals
• Fourier transform
• modulation
• frequency domain analysis of LTI systems
• filters
• sampling and DFT
• Matlab and CAD exercises

Teaching methods

Lectures
Exercises & homework
Exams

Learning materials and recommended literature

Lecture recordings
Lecture materials
Erwin Kreyszig : Advanced Engineering Mathematics

Exam dates and retake possibilities

Two exams on last week of the course

Student workload

Three equal parts
- Differential and integral calculus in multivariable functions (~135 h)
- Control engineering and applied mathematics (~135 h)
- Integral transformation and signal theory (~135 h)
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~90 h lectures
~300 h studying, exercises and homework
~8 h exams

Content scheduling

3 x 4 h/week, evening lectures

Assessment methods and criteria

Exercises
Homework
Exams

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student understands the criteria and principles of the expertise development. The student has completed the required learning exercises in minimum requirement level. His/her competences have developed in a way that he/she may complete the remaining studies and finally work in a suitable job position related to this field.

Assessment criteria, good (3)

The student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. The student has completed the required learning exercises in good or satisfactory level. The student is able to define the course concepts and models and is able to justify the analysis. The student is able to apply their knowledge in study and work situations. The student understands the importance of expertise in the field and is able to analyze his/her own expertise.

Assessment criteria, excellent (5)

The student has achieved the objectives of the course with excellent marks. The student master commendably the course subject area’s concepts and models. The student has completed the required learning exercises in good or excellent level. The student is able to make justified and fluent analysis and to present concrete development measures. The student is well prepared to apply their knowledge study and work situations. Students are able to analyze the expertise and the evolvement of their own expertise.