Data-driven modeling, filtering and control : methods and applications
Contributor(s): Novara, Carlo [ed.] | Formentin, Simone [ed.].
Series: IET control, robotics and sensors series. ; v.123.Publisher: London The Institution of Engineering and Technology 2019Description: x, 289p.ISBN: 9781785617126.Subject(s): System design -- Data processing | Systems engineering -- Data processing | Automatic control -- Data processingDDC classification: 629.895 | D262 Summary: The scientific research in many engineering fields has been shifting from traditional first-principle-based to data-driven or evidence-based theories. The latter methods may enable better system design, based on more accurate and verifiable information. In the era of big data, IoT and cyber-physical systems, this subject is of growing importance, as data-driven approaches are key enablers to solve problems that could not be addressed by standard approaches. This book presents a number of innovative data-driven methodologies, complemented by significant application examples, to show the potential offered by the most recent advances in the field. Applicable across a range of disciplines, the topics discussed here will be of interest to scientists, engineers and students in automatic control and learning systems, automotive and aerospace engineering, electrical engineering and signal processing.| Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Reference
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PK Kelkar Library, IIT Kanpur | Reference | 629.895 D262 (Browse shelf) | Not for loan | A186221 |
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The scientific research in many engineering fields has been shifting from traditional first-principle-based to data-driven or evidence-based theories. The latter methods may enable better system design, based on more accurate and verifiable information.
In the era of big data, IoT and cyber-physical systems, this subject is of growing importance, as data-driven approaches are key enablers to solve problems that could not be addressed by standard approaches. This book presents a number of innovative data-driven methodologies, complemented by significant application examples, to show the potential offered by the most recent advances in the field. Applicable across a range of disciplines, the topics discussed here will be of interest to scientists, engineers and students in automatic control and learning systems, automotive and aerospace engineering, electrical engineering and signal processing.
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