English | 2019 | ISBN: 978-1785617126 | 296 Pages | PDF | 42 MB
Research in the field of system identification and control has been shifting from traditional model-based to data-driven or evidence-based theories. The latter methods enable better designs based on more direct and accurate data-based information and verifiable data. 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 previous 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 researchers, engineers and students in automatic control, learning systems, automotive and aerospace engineering, electrical engineering and signal processing.
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