- Fuzzy control: fuzzy sets and operators, membership function, fuzzification, fuzzy implication, defuzzification, basic working principle of fuzzy controllers, typical applications.
- Artificial intelligence and its application to control, modelling and diagnosis: supervised learning, unsupervised learning, Back-Propagation algorithm, radial basis function network, self-organizing map, support vector machine, reinforcement learning, training and validation of artificial neural networks, typical application scenarios.
- Genetic algorithms and evolutionary algorithms: stochastic optimization approaches, selection of parameters, application in optimization, application in modelling, control and diagnosis.
Methods of Soft Control (M, 3.0 LP)
|Module Number||Module Name||CP (Effort)|
|EIT-AUT-453-M-7||Methods of Soft Control||3.0 CP (90 h)|
|CP, Effort||3.0 CP = 90 h|
|Position of the semester||1 Sem. in WiSe|
|Level|| Master (Advanced)|
|Area of study||[EIT-AUT] Automation Control|
|Reference course of study||[EIT-88.781-SG#2010] M.Sc. Electrical and Computer Engineering |
|Type/SWS||Course Number||Title||Choice in |
|SL||SL is |
required for exa.
Methods of Soft Control
|P||28 h||62 h||-||-||PL1||3.0||WiSe|
- About [EIT-AUT-453-K-7]: Title: "Methods of Soft Control"; Presence-Time: 28 h; Self-Study: 62 h
Examination achievement PL1
- Form of examination: written exam (Klausur) (90 Min.)
- Examination Frequency: each semester
Evaluation of grades
The grade of the module examination is also the module grade.
Competencies / intended learning achievements
After completing this module you can...
- ... explain the difference between classical control methods and computational intelligence based control methods (such as fuzzy control, artificial intelligence, genetic and evolutionary algorithms).
- ... summarize and explain computational intelligence based control methods and explain their basic ideas, the advantage and the disadvantages.
- ... identify typical application areas of these approaches.
- ... apply these methods to solve specific problems in modeling, control and diagnosis.
Requirements for attendance (informal)
- [EIT-AUT-457-M-4] Fundamentals of Automation (M, 5.0 LP)
- [EIT-LRS-504-M-3] Linear Control (M, 5.0 LP)
Requirements for attendance (formal)
References to Module / Module Number [EIT-AUT-453-M-7]
|Course of Study||Section||Choice/Obligation|
|[EIT-88.781-SG#2010] M.Sc. Electrical and Computer Engineering ||Specialization Modules||[P] Compulsory|
|[EIT-88.?-SG#2021] M.Sc. Electrical and Computer Engineering ||Major Automation & Control (AUT)||[P] Compulsory|
|[EIT-88.A20-SG#2021] M.Sc. European Master in Embedded Computing Systems (EMECS) ||Elective Subjects||[W] Elective Module|
|[EIT-88.?-SG#2021] M.Sc. Automation and Control (A&C) ||A&C Core Courses||[P] Compulsory|
|[EIT-88.?-SG#2021] M.Sc. Embedded Computing Systems (ESY) ||Elective Subjects||[W] Elective Module|