Data driven strategies theory and applications / Wang Jianhong, Ricardo A. Ramirez-Mendoza, Ruben Morales-Menendez.

Author/creator Wang, Jianhong
Other author Ram©Ưrez-Mendoza, Ricardo A.
Other author Morales-Men©♭ndez, Rub©♭n.
Format Electronic
EditionFirst edition.
Publication InfoBoca Raton : CRC Press/Taylor & Francis Group, 2023.
Descriptionix, 352 pages : illustrations ; 25 cm
Supplemental ContentFull text available from Taylor & Francis eBooks
Subjects

Abstract "One of the main problems in science and engineering is to provide a quantitative description of the systems under investigation, leveraging collected noisy data. Such a description may be a complete mathematical model or a mechanism to return controllers corresponding to new, unseen inputs. Recent advances in the theories are described in detail, along with their applications in engineering. The book aims to develop model-free system analysis and control strategies, i.e., data-driven control from theoretical analysis and engineering applications based only on measured data. The study aims to develop system identification, and combination in advanced control theory, i.e., data-driven control strategy as system and controller are generated from measured data directly. The book covers the development of system identification and its combination in advanced control theory, i.e., data-driven control strategy, as they all depend on measured data. Firstly, data-driven identification is developed for the closed-loop, nonlinear system and model validation, i.e., obtaining model descriptions from measured data. Secondly, the data-driven idea is combined with some control strategies to be considered data-driven control strategies, such as data-driven model predictive control, data-driven iterative tuning control, and data-driven subspace predictive control. Thirdly data-driven identification and data-driven control strategies are applied to interested engineering. In this context, the book provides algorithms to perform state estimation of dynamical systems from noisy data and some convex optimization algorithms through identification and control problems"-- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2022046455
ISBN9780367746599 (hbk.)
ISBN9780367750084 (pbk.)
ISBN(ebk.)

Availability

Library Location Call Number Status Item Actions
Electronic Resources Access Content Online ✔ Available