| Course Code: |
7203C |
| Course Type: |
Theory & Laboratory |
| Course Category: |
Core Module |
| Hours per Week: |
5 (Theory 3, Lab 2) |
| Credit Units: |
5 |
| Semester: |
G |
Aims and Scope
This
course aims to introduce students into the concepts of modeling and
optimization of systems, allowing them to acquire skills on the identification
of equations of state, the identification of optimization criteria and the selection
of algorithmic optimization methods, moving from verbal to numeric variables, modeling
and optimization of systems with fuzzy logic.
Course Description
Theory: The
modeling of systems. Modeling diagram links with causality. Optimization
methods. Linear and dynamic programming. Applications in energy systems.
Simulation and optimization of energy policy. Fuzzy logic. Optimization models
with fuzzy logic. Simulation and evaluation of models.
Laboratory: The laboratory part of the course includes the
use of Matlab Simulink and Fuzzy Logic toolbox for the simulation and
optimization systems.
Expected Course Outcome
After the
end of the course students will be able to:
- To
derive the equations that simulate a system
- Specify
the criteria for optimization
- To
apply the appropriate optimization method
- To
express numeric variables with verbal variable
- To
design simulation rules and apply optimization with fuzzy logic
Bibliography
Greek:
- Κρικέλης Ν. “Μοντελοποίηση και Βέλτιστος Έλεγχος Συστημάτων”, Εκδόσεις Fountas,2003.
- Ροβέρτος-Ε. Κινγκ, “Ευφυής Έλεγχος”, Εκδόσεις Τζιολα, 2004.
English:
- Baldwin, J. F., “Fuzzy sets and Expert systems”, Inf. Sci. (N. Y.), 36, 123, 1985.
- Constantin von Altrock, “Fuzzy Logic, Neurofuzzy Applications”, Prentice Hall,1995.
- Jamshidi M. Et al, “Fuzzy Logic and Control”, Prentice Hall, 1993.
- Zadeh, L. A., “The role of fuzzy logic in the management of uncertainty in expert systems”, Fuzzy Set and Systems, 1983.
- Burley, D.M. , “Studies in Optimization”, International Textbook Company, 1974.
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