Robust Fault Diagnosis and Fault Tolerant Control of Wind Turbines | Data-driven and model-based approaches. This item is unavailable.
Language: English
Published by Scholars' Press, 2016
- Softcover
- New

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Softcover
Condition: New
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Robust Fault Diagnosis and Fault Tolerant Control of Wind Turbines | Data-driven and model-based approaches | Saverio Farsoni (u. a.) | Taschenbuch | 108 S. | Englisch | 2016 | Scholars' Press | EAN 9783659838019 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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- Title
- Robust Fault Diagnosis and Fault Tolerant Control of Wind Turbines | Data-driven and model-based approaches
- Author
- Saverio Farsoni (u. a.)
- Publisher
- Scholars' Press
- Publication year
- 2016
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3659838012
- ISBN 13
- 9783659838019
- Item weight
- 179 grams
- Dimensions
- 220 x 150 x 8 mm
- Seller catalogs
- Bücher
The increasing demand for energy generation from renewable sources has led to a growing attention on wind turbines. They represent very complex systems which require reliability, availability, maintainability, safety and, above all, efficiency on the generation of electrical power. Thus, new research challenges arise in the context of modelling and control. Advanced sustainable control systems can provide the optimisation of energy conversion and guarantee the desired performances even in presence of possible anomalous working condition, caused by unexpected faults. This monograph deals with the fault diagnosis and the fault tolerant control of wind turbines, and it proposes novel solutions to the problem of earlier fault detection and accommodation. The developed fault tolerant controller is mainly based on a fault diagnosis module, which provides the on-line information on the faulty or fault-free status of the system, so that the control action can be compensated. The design of the fault estimators involves different approaches, as they offer an effective tool for coping with a poor analytical knowledge of the system dynamics, together with noise and disturbances.
"Synopsis" may belong to another edition of this title.
About the Author
Saverio Farsoni: (2012) Informatics and Automation Engineering M.Sc. and (2016) Information Sciences Ph.D at the University of Ferrara (Italy). Research fellow. Silvio Simani: (1996) Electronic Engineering M.Sc. and (2000) Information Sciences Ph.D at the University of Ferrara and Modena. Professor. They work on FDI and FTC for dynamic processes.
"About the title" may belong to another edition of this title.