Administracja Centralna Uczelni - Wymiana międzynarodowa (S1)
Sylabus przedmiotu Essentials of Fuzzy Logic and its Application to System Modeling and Control:
Informacje podstawowe
| Kierunek studiów | Wymiana międzynarodowa | ||
|---|---|---|---|
| Forma studiów | studia stacjonarne | Poziom | pierwszego stopnia |
| Tytuł zawodowy absolwenta | |||
| Obszary studiów | — | ||
| Profil | |||
| Moduł | — | ||
| Przedmiot | Essentials of Fuzzy Logic and its Application to System Modeling and Control | ||
| Specjalność | przedmiot wspólny | ||
| Jednostka prowadząca | Katedra Metod Sztucznej Inteligencji i Matematyki Stosowanej | ||
| Nauczyciel odpowiedzialny | Marcin Pluciński <Marcin.Plucinski@zut.edu.pl> | ||
| Inni nauczyciele | Marcin Korzeń <Marcin.Korzen@zut.edu.pl>, Joanna Kołodziejczyk <Joanna.Kolodziejczyk@zut.edu.pl>, Wojciech Sałabun <wsalabun@wi.zut.edu.pl> | ||
| ECTS (planowane) | 6,0 | ECTS (formy) | 6,0 |
| Forma zaliczenia | zaliczenie | Język | angielski |
| Blok obieralny | — | Grupa obieralna | — |
Formy dydaktyczne
Wymagania wstępne
| KOD | Wymaganie wstępne |
|---|---|
| W-1 | Basic knowledge of high mathematics |
Cele przedmiotu
| KOD | Cel modułu/przedmiotu |
|---|---|
| C-1 | Acquirement of competence and practice in construction of fuzzy models of systems, fuzzy calculations and fuzzy control of plants |
Treści programowe z podziałem na formy zajęć
| KOD | Treść programowa | Godziny |
|---|---|---|
| laboratoria | ||
| T-L-1 | Discovering by student fuzzy phenomena, fuzzy variables, fuzzy notions in the world | 2 |
| T-L-2 | Constructing membership functions for own detected uncertain values from science, technique, medicine, economics, biology etc. Describing membership fumctions by mathematical formulas. Trasformation of vertical membership functions into horizontal functions. | 3 |
| T-L-3 | Constructing rule bases for real systems and checking their logical consistence | 2 |
| T-L-4 | Training in fuzzyfication, rule premises evaluation, conclusion activation of individual rules, aggregation of individual rule conclusions in one resulting conclusion of the rule base and its defuzzification | 4 |
| T-L-5 | Constructing fuzzy models for real systems. | 4 |
| T-L-6 | Calculation of the fuzzy model output for given values of its inputs for models of various dimensionality | 4 |
| T-L-7 | Constructing neuro-fuzzy networks for a given fuzzy model | 2 |
| T-L-8 | Constructing expert fuzzy controllers for a given real plant | 6 |
| T-L-9 | Constructing fuzzy controllers on the basis of a plant-model | 3 |
| 30 | ||
| wykłady | ||
| T-W-1 | Diffrence between classical and fuzzy logic. Examples of fuzziness in the real world. Necessity of fuzziness use. Short history of fuzzy logic development. | 4 |
| T-W-2 | Mathematical models of fuzzy linguistic and numerical evaluations : membership functions. Examples of membership functions. Vertical and horizontal models of membership functions. Identification of membership functions by experts. Typical errors made during the identification. | 4 |
| T-W-3 | Classical (vertical) and new, horizontal fuzzy arithmetic. Transformation of vertical in horizontal membership functions. Examples of calculations. Granular arithmetic and mathematics. | 4 |
| T-W-4 | Fuzzy models of systems. Components of fuzzy models: fuzzification, premise evaluation, determination of activated membership functions of paricular rules, determining of the resulting membership function of the rule base and its defuzzification. | 6 |
| T-W-5 | Constructing fuzzy models for chosen real problems and calculating model ouputs for give model inputs. | 4 |
| T-W-6 | Neuro-fuzzy networks as self-learning fuzzy models. | 2 |
| T-W-7 | Fuzzy control and its structure. Classic, expert fuzzy control and control based on the model of the controlled plant. | 4 |
| T-W-8 | Examples of real applications of fuzzy logic. | 2 |
| 30 | ||
Obciążenie pracą studenta - formy aktywności
| KOD | Forma aktywności | Godziny |
|---|---|---|
| laboratoria | ||
| A-L-1 | Participating in laboratory training | 30 |
| A-L-2 | Solving home tasks given by the academician | 40 |
| A-L-3 | Studying literature referring to the laboratory problems | 25 |
| A-L-4 | Consultations connected with laboratory problems solved by the student | 25 |
| 120 | ||
| wykłady | ||
| A-W-1 | Participating in the lectures | 30 |
| A-W-2 | Home studying of the lecture text and of reccomended literature | 26 |
| A-W-3 | Personal consultations devoted to explanation of difficult parts of lectures | 4 |
| 60 | ||
Metody nauczania / narzędzia dydaktyczne
| KOD | Metoda nauczania / narzędzie dydaktyczne |
|---|---|
| M-1 | Informational lecture with presentations |
| M-2 | Laboratory training in individual solving of problems delivered by an academition |
Sposoby oceny
| KOD | Sposób oceny |
|---|---|
| S-1 | Ocena podsumowująca: Lectures: summarizing evaluation of knowledge assimilated by student in form of an exam and of evaluation the student activity shown during lectures |
| S-2 | Ocena formująca: Laboratory: forming evaluation of the student based on the student activity and ability shown at solving problems given by an academician |
Zamierzone efekty uczenia się - wiedza
| Zamierzone efekty uczenia się | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WI_1-_??_W01 The student has knowledge about fuzzy sets, fuzzy modelling and their practical applications. | — | — | C-1 | T-W-1, T-W-2, T-W-3, T-W-4, T-W-5, T-W-6, T-W-7, T-W-8 | M-1 | S-1 |
Zamierzone efekty uczenia się - umiejętności
| Zamierzone efekty uczenia się | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WI_1-_??_U01 The student has the ability to analyse fuzzy models work, to create them for chosen real problems, and to use them in control systems. | — | — | C-1 | T-L-1, T-L-2, T-L-3, T-L-4, T-L-5, T-L-6, T-L-7, T-L-8, T-L-9 | M-2 | S-2 |
Kryterium oceny - wiedza
| Efekt uczenia się | Ocena | Kryterium oceny |
|---|---|---|
| WM-WI_1-_??_W01 The student has knowledge about fuzzy sets, fuzzy modelling and their practical applications. | 2,0 | |
| 3,0 | The student has the basic knowledge about fuzzy systems and fuzzy modelling. | |
| 3,5 | ||
| 4,0 | ||
| 4,5 | ||
| 5,0 |
Kryterium oceny - umiejętności
| Efekt uczenia się | Ocena | Kryterium oceny |
|---|---|---|
| WM-WI_1-_??_U01 The student has the ability to analyse fuzzy models work, to create them for chosen real problems, and to use them in control systems. | 2,0 | |
| 3,0 | The student has the basic ability to create fuzzy models and to analyse their work. | |
| 3,5 | ||
| 4,0 | ||
| 4,5 | ||
| 5,0 |
Literatura podstawowa
- Andrzej Piegat, Fuzzy modeling and control, Physica-Verlag, A Springer-Verlag Company, 2001, 1
- Witold Pedrycz, Fernando Gomide, Fuzzy systems engineering, Wiley-Interscience, Hoboken, New Jersey, USA, 2007, 1
Literatura dodatkowa
- Y. Bai, H. Zhuang, D. Wang (editors), Advanced fuzzy logic technologies in industriel applications, Springer, Berlin, Heidelberg, New York, 2006, 1