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001445337 001__ 1445337
001445337 003__ OCoLC
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001445337 019__ $$a1305439807$$a1305912412$$a1306025413$$a1306057993
001445337 020__ $$a9789811904646$$q(electronic bk.)
001445337 020__ $$a9811904642$$q(electronic bk.)
001445337 020__ $$z9789811904639
001445337 020__ $$z9811904634
001445337 0247_ $$a10.1007/978-981-19-0464-6$$2doi
001445337 035__ $$aSP(OCoLC)1305166402
001445337 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dEBLCP$$dOCLCO$$dOCLCF$$dUKAHL$$dOCLCQ
001445337 049__ $$aISEA
001445337 050_4 $$aQA402.3$$b.C55 2022
001445337 08204 $$a629.8/312$$223
001445337 1001_ $$aChi, Ronghu,$$eauthor.
001445337 24510 $$aDiscrete-time adaptive iterative learning control :$$bfrom model-based to data-driven /$$cRonghu Chi, Na Lin, Huimin Zhang, Ruikun Zhang.
001445337 264_1 $$aSingapore :$$bSpringer,$$c[2022]
001445337 264_4 $$c©2022
001445337 300__ $$a1 online resource :$$billustrations (chiefly color).
001445337 336__ $$atext$$btxt$$2rdacontent
001445337 337__ $$acomputer$$bc$$2rdamedia
001445337 338__ $$aonline resource$$bcr$$2rdacarrier
001445337 4901_ $$aIntelligent control and learning systems,$$x2662-5466 ;$$vvolume 1
001445337 504__ $$aIncludes bibliographical references.
001445337 5050_ $$aChapter 1: Introduction -- Part 1: Model-based Discrete-time Adaptive ILC -- Chapter 2: Discrete-time Adaptive ILC for Linear Parametric Systems -- Chapter 3: Discrete-time Adaptive ILC for Higher order Parametric Systems -- Chapter 4: Data-weighted Discrete-time Adaptive ILC Chapter -- 5: Discrete-time Adaptive ILC for Nonparametric Nonlinear Systems Part 2: Data-driven Discrete-time Adaptive ILC Chapter -- 6: Neural Network based Discrete-time Adaptive ILC -- Chapter 7: Data-driven Discrete-time Adaptive ILC for Nonaffined Nonlinear Systems -- Chapter 8: Multi-input Enhanced Data-driven Discrete-time Adaptive ILC -- Chapter 9: High-order Internal Model based Data-driven Terminal Adaptive ILC -- Chapter 10: Conclusions Appendices.
001445337 506__ $$aAccess limited to authorized users.
001445337 520__ $$aThis book belongs to the subject of control and systems theory. The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book begins with the design and analysis of model-based DAILC methods by referencing the tools used in the discrete-time adaptive control theory. To overcome the extreme difficulties in modeling a complex system, the data-driven DAILC methods are further discussed by building a linear parametric data mapping between two consecutive iterations. Other significant improvements and extensions of the model-based/data-driven DAILC are also studied to facilitate broader applications. The readers can learn the recent progress on DAILC with consideration of various applications. This book is intended for academic scholars, engineers and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.
001445337 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed April 5, 2022).
001445337 650_0 $$aControl theory.
001445337 650_0 $$aIterative methods (Mathematics)
001445337 650_0 $$aDiscrete-time systems.
001445337 650_6 $$aThéorie de la commande.
001445337 650_6 $$aItération (Mathématiques)
001445337 650_6 $$aSystèmes échantillonnés.
001445337 655_0 $$aElectronic books.
001445337 7001_ $$aLin, Na,$$eauthor.
001445337 7001_ $$aZhang, Huimin,$$eauthor.
001445337 7001_ $$aZhang, Ruikun,$$eauthor.
001445337 77608 $$iPrint version: $$z9811904634$$z9789811904639$$w(OCoLC)1294139702
001445337 830_0 $$aIntelligent control and learning systems ;$$vvolume 1.$$x2662-5466
001445337 852__ $$bebk
001445337 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-0464-6$$zOnline Access$$91397441.1
001445337 909CO $$ooai:library.usi.edu:1445337$$pGLOBAL_SET
001445337 980__ $$aBIB
001445337 980__ $$aEBOOK
001445337 982__ $$aEbook
001445337 983__ $$aOnline
001445337 994__ $$a92$$bISE