Veranstaltungsarten (SWS)
Vorlesung: 2 │ Übung: 1 │ Praktikum: 0 │ Seminar: 0
Prüfungsnummer: ZKA 41132
Lehrform:
Sprache: Deutsch
Turnus: SS
ECTS: 4
Prüfungsleistung Klausur (90 min.)
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Beschreibung:

Hohe Zuverlässigkeit und Verfügbarkeit spielen in der Automatisierungstechnik eine wichtige Rolle. Schlüsseltechnologien sind Fehlerdiagnose sowie fehlertolerante Systeme. Im Rahmen dieser Lehrveranstaltung werden statistische, daten-basierte und modellgestützte Methoden zur Fehlerdiagnose und zur fehlertoleranten Regelung sowie die erforderlichen Entwurfsalgorithmen und Tools vorgestellt.

Lernziele:

Die Studierenden sollen in der Lage, statistische, daten-basierte und modellgestützte Methoden zur Fehlerdiagnose und zur fehlertoleranten Regelung anzuwenden.

Literatur:

Steven X. Ding, Model-based fault diagnosis techniques, Springer-Verlag, 2008.

Selected publications in leading international journals.

Vorleistung:
Infolink:
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Description:

A very critical and important issue concerning the design of automatic control systems with increasing complexity is to guarantee a high system performance over a wide operating range and meeting the requirements on system reliability and dependability. As one of the key technologies for the problem solution, advanced fault detection and identification (FDI) technology and fault tolerant systems (FTC) are receiving considerable attention. The objective of this course is to introduce basic model based FDI and fault tolerant schemes, advanced analysis and design algorithms and the needed tools.
The course consists of 6 parts.
Part I: Basic fault detection problems and the associated solutions.
The following two topics are addressed in this part:
• Basic statistical methods for change/fault detection
• Basic deterministic methods for change/fault detection
Part II: Basic data-driven methods
The following two topics are addressed:
• Basic data-driven methods for statistic processes
• A basic data-driven method for deterministic processes
Part III: model-based FDI methods
• Two essential problems
• Essentials: Modelling and residual generation
• Fault detection in stochastic systems
• Fault detection in deterministic systems
Part IV: Data-driven design of dynamic FDI systems
• Subspace identification technique (SIT) aided design of observer-based FDI systems
Part V: Fault isolation and identification schemes
• Basic isolation and identification methods
• Methods to a structural fault isolation (for dynamic processes)
Part VI: Fault-tolerant systems

Learning Targets:

The students should be able to apply statistical, data-driven and model-based FDI and FTC methods to real cases.

Literature:

Steven X. Ding, Model-based fault diagnosis techniques, Springer-Verlag, 2008.

Selected publications in leading international journals.

Pre-Qualifications:
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