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Course info
KKY / AŘ2
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Course description
Department/Unit / Abbreviation
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KKY
/
AŘ2
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Automatic Control 2
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Form of course completion
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Exam
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Form of course completion
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Exam
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Accredited / Credits
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Yes,
3
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
2
[Hours/Week]
Tutorial
1
[Hours/Week]
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Included in study average
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YES
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Language of instruction
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Czech
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Occ/max
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Summer semester
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0 / 38
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0 / 9
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0 / 2
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Included in study average
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YES
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Winter semester
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0 / -
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0 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Summer semester
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Semester taught
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Summer semester
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Minimum (B + C) students
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10
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
1|2|3|4 |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
No
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Fundamental theoretical course |
No
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Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
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None
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Preclusive courses
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N/A
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Prerequisite courses
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N/A
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Informally recommended courses
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KKY/AŘ or KKY/AŘ1 or KKY/TŘ
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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The purpose of the course is introducing students to knowledge of automatic control linear discrete dynamical systems, logical systems and fuzzy systems too.
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Requirements on student
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Credit: Elaborate a two semestral work - measurement protocol. Successfully pass a one check test
during semester.
Exam: Oral and written examination on the subject is requested.
Note: When re-writing the subject, the credit before the exam is not approved.
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Content
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Subject build up the theory of automatic control of discrete linear dynamical systems. The basics of the logical systems, nonlinear systems and fuzzy systems are mention too. Deal with: Discretization of continuous signal, discrete time and sampling theorem. Discrete system description techniques, difference equation and z-transfer function. Stability of discrete systems, Jury's stability test. Quality and design of the PSD controllers. Design of the logical systems, Boole's algebra, Karnaugh's map minimization. Theory of nonlinear systems, Ljapunov's theorem of stability. Fuzzy systems, fuzzy versus crisp sets, membership function, fuzzyfication, inferrence and defuzzification rules, fuzzy logic control possibilities.
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Activities
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Fields of study
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Guarantors and lecturers
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Literature
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Contact hours
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26
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Preparation for formative assessments (2-20)
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4
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Practical training (number of hours)
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13
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Preparation for an examination (30-60)
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35
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Total
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78
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
have a basic knowledge of the mathematical analysis and linear algebra |
have a basic knowledge of introductory college courses in Physics and Electrical Engineering |
have a basic knowledge of computers and programming at the introductory college courses (Matlab/Simulink) |
know the basic principles of automatic control linear dynamical systems (course KKY / AŘ1) |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
actively use basic methods of mathematical analysis and linear algebra |
independently solve given the simulation tasks in the laboratory |
in the form of technical reports describe and process the results of own laboratory work |
solve the given laboratory simulation tasks using tools Matlab-Simulink |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
N/A |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
classify basic types of systems (especially discrete systems, nonlinear systems, fuzzy logic systems and systems) |
solve practical problems to design basic types of controllers and their optimal setting |
Skills - skills resulting from the course: |
recognize basic control tasks and exchange of information in different systems (especially discrete systems, logic systems and fuzzy systems) |
discretization of the analogue signal (discrete time and sampling period) |
describe discrete linear systems (inner and outer systems description - differential equations, transfer function in the Z-transform, state space approach) |
acces dynamic and frequency characteristics of discrete systems |
acces stability and quality of discrete systems (Jury criterion) |
correctly apply the principles of automatic control for synthesis discrete optimal systems of automatic control (regulators), particularly for industrial applications. |
describe nonlinear system and evaluate their stability by Lyapunov method |
design combinational logic circuits using Boolean algebra (ÚNDF, minimization, NAND and NOR implementation) |
describe of the fuzzy system; fuzzy sets, fuzzy approximation; fuzzification, Mamdani inference, defuzzification |
design a simple fuzzy controller in Matlab (Fuzzy Logic Toolbox) |
Competences - competences resulting from the course: |
N/A |
N/A |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Test |
Skills demonstration during practicum |
Individual presentation at a seminar |
Skills - skills achieved by taking this course are verified by the following means: |
Skills demonstration during practicum |
Individual presentation at a seminar |
Combined exam |
Competences - competence achieved by taking this course are verified by the following means: |
Individual presentation at a seminar |
Seminar work |
Combined exam |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Practicum |
Laboratory work |
Self-study of literature |
Skills - the following training methods are used to achieve the required skills: |
Lecture |
Laboratory work |
One-to-One tutorial |
Task-based study method |
Competences - the following training methods are used to achieve the required competences: |
Lecture |
Laboratory work |
Skills demonstration |
Interactive lecture |
Students' portfolio |
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