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US$ 11.91
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Add to baskethardcover. Condition: Very Good. Iterative Learning Control with Passive Incomplete Information: Algorithms Design and Convergence Analysis This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
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US$ 10.67
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Add to basketCondition: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
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US$ 10.67
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Add to basketCondition: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind.
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Iterative Learning Control with Passive Incomplete Information. Algorithms Design and Convergence Analysis.
Published by Singapore, Springer., 2018
ISBN 10: 9811082669 ISBN 13: 9789811082665
Language: English
Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Association Member: GIAQ ILAB VDA
Seller rating 5 out of 5 stars
US$ 14.37
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Add to basketXIV, 294 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.
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Iterative Learning Control with Passive Incomplete Information. Synthesis and Analysis.
Published by Singapore, Springer., 2019
ISBN 10: 9811361355 ISBN 13: 9789811361357
Language: English
Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Association Member: GIAQ ILAB VDA
Seller rating 5 out of 5 stars
US$ 22.75
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Add to basketXIV, 256 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.
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US$ 168.16
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US$ 178.51
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Iterative Learning Control for Systems with Iteration-Varying Trial Lengths: Synthesis and Analysis
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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US$ 178.02
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US$ 185.98
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Add to basketHardcover. Condition: Brand New. 310 pages. 9.25x6.10x0.94 inches. In Stock.
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Iterative Learning Control: Analysis, Design, Integration and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 192.40
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Iterative Learning Control: Analysis, Design, Integration and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 192.40
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Iterative Learning Control for Systems with Iteration-Varying Trial Lengths : Synthesis and Analysis
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Condition: New. pp. 308.
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Iterative Learning Control with Passive Incomplete Information : Algorithms Design and Convergence Analysis
Published by Springer Nature Singapore, Springer Nature Singapore, 2018
ISBN 10: 9811341052 ISBN 13: 9789811341052
Language: English
US$ 184.29
Convert currencyUS$ 35.27 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents an in-depth discussion of iterative learning control (ILC) with passive incomplete information, highlighting the incomplete input and output data resulting from practical factors such as data dropout, transmission disorder, communication delay, etc.-a cutting-edge topic in connection with the practical applications of ILC. It describes in detail three data dropout models: the random sequence model, Bernoulli variable model, and Markov chain model-for both linear and nonlinear stochastic systems. Further, it proposes and analyzes two major compensation algorithms for the incomplete data, namely, the intermittent update algorithm and successive update algorithm. Incomplete information environments include random data dropout, random communication delay, random iteration-varying lengths, and other communication constraints. With numerous intuitive figures to make the content more accessible, the book explores several potential solutions to this topic, ensuring that readers are not only introduced to the latest advances in ILC for systems with random factors, but also gain an in-depth understanding of the intrinsic relationship between incomplete information environments and essential tracking performance. It is a valuable resource for academics and engineers, as well as graduate students who are interested in learning about control, data-driven control, networked control systems, and related fields.
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Iterative Learning Control for Systems with Iteration-Varying Trial Lengths : Synthesis and Analysis
Published by Springer Nature Singapore, Springer Nature Singapore, 2019
ISBN 10: 9811361355 ISBN 13: 9789811361357
Language: English
US$ 184.29
Convert currencyUS$ 35.89 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a comprehensive and detailed study on iterative learning control (ILC) for systems with iteration-varying trial lengths. Instead of traditional ILC, which requires systems to repeat on a fixed time interval, this book focuses on a more practical case where the trial length might randomly vary from iteration to iteration. The iteration-varying trial lengths may be different from the desired trial length, which can cause redundancy or dropouts of control information in ILC, making ILC design a challenging problem. The book focuses on the synthesis and analysis of ILC for both linear and nonlinear systems with iteration-varying trial lengths, and proposes various novel techniques to deal with the precise tracking problem under non-repeatable trial lengths, such as moving window, switching system, and searching-based moving average operator. It not only discusses recent advances in ILC for systems with iteration-varying trial lengths, but also includes numerousintuitive figures to allow readers to develop an in-depth understanding of the intrinsic relationship between the incomplete information environment and the essential tracking performance. This book is intended for academic scholars and engineers who are interested in learning about control, data-driven control, networked control systems, and related fields. It is also a useful resource for graduate students in the above field.
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Iterative Learning Control with Passive Incomplete Information : Algorithms Design and Convergence Analysis
Published by Springer Nature Singapore, Springer Nature Singapore, 2018
ISBN 10: 9811082669 ISBN 13: 9789811082665
Language: English
US$ 184.29
Convert currencyUS$ 36.20 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents an in-depth discussion of iterative learning control (ILC) with passive incomplete information, highlighting the incomplete input and output data resulting from practical factors such as data dropout, transmission disorder, communication delay, etc.-a cutting-edge topic in connection with the practical applications of ILC. It describes in detail three data dropout models: the random sequence model, Bernoulli variable model, and Markov chain model-for both linear and nonlinear stochastic systems. Further, it proposes and analyzes two major compensation algorithms for the incomplete data, namely, the intermittent update algorithm and successive update algorithm. Incomplete information environments include random data dropout, random communication delay, random iteration-varying lengths, and other communication constraints. With numerous intuitive figures to make the content more accessible, the book explores several potential solutions to this topic, ensuring that readers are not only introduced to the latest advances in ILC for systems with random factors, but also gain an in-depth understanding of the intrinsic relationship between incomplete information environments and essential tracking performance. It is a valuable resource for academics and engineers, as well as graduate students who are interested in learning about control, data-driven control, networked control systems, and related fields.
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US$ 196.96
Convert currencyUS$ 36.09 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Iterative Learning Control (ILC) differs from most existing control methods in the sense that, it exploits every possibility to incorporate past control informa tion, such as tracking errors and control input signals, into the construction of the present control action. There are two phases in Iterative Learning Control: first the long term memory components are used to store past control infor mation, then the stored control information is fused in a certain manner so as to ensure that the system meets control specifications such as convergence, robustness, etc. It is worth pointing out that, those control specifications may not be easily satisfied by other control methods as they require more prior knowledge of the process in the stage of the controller design. ILC requires much less information of the system variations to yield the desired dynamic be haviors. Due to its simplicity and effectiveness, ILC has received considerable attention and applications in many areas for the past one and half decades. Most contributions have been focused on developing new ILC algorithms with property analysis. Since 1992, the research in ILC has progressed by leaps and bounds. On one hand, substantial work has been conducted and reported in the core area of developing and analyzing new ILC algorithms. On the other hand, researchers have realized that integration of ILC with other control techniques may give rise to better controllers that exhibit desired performance which is impossible by any individual approach.
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US$ 256.87
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Add to basketHardcover. Condition: Brand New. 272 pages. 9.25x6.10x0.90 inches. In Stock.
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US$ 213.31
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US$ 237.13
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Add to basketHardcover. Condition: New. New. book.
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US$ 248.76
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US$ 279.33
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Add to basketPaperback. Condition: Brand New. reprint edition. 308 pages. 9.25x6.10x0.70 inches. In Stock.
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US$ 263.96
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Add to basketPaperback. Condition: Like New. Like New. book.
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Iterative Learning Control : Analysis, Design, Integration and Applications
Published by Springer Us Jul 1998, 1998
ISBN 10: 0792382137 ISBN 13: 9780792382133
Language: English
US$ 296.90
Convert currencyUS$ 36.84 shipping from Germany to U.S.A.Quantity: 2 available
Add to basketBuch. Condition: Neu. Neuware - Iterative Learning Control (ILC) differs from most existing control methods in the sense that, it exploits every possibility to incorporate past control informa tion, such as tracking errors and control input signals, into the construction of the present control action. There are two phases in Iterative Learning Control: first the long term memory components are used to store past control infor mation, then the stored control information is fused in a certain manner so as to ensure that the system meets control specifications such as convergence, robustness, etc. It is worth pointing out that, those control specifications may not be easily satisfied by other control methods as they require more prior knowledge of the process in the stage of the controller design. ILC requires much less information of the system variations to yield the desired dynamic be haviors. Due to its simplicity and effectiveness, ILC has received considerable attention and applications in many areas for the past one and half decades. Most contributions have been focused on developing new ILC algorithms with property analysis. Since 1992, the research in ILC has progressed by leaps and bounds. On one hand, substantial work has been conducted and reported in the core area of developing and analyzing new ILC algorithms. On the other hand, researchers have realized that integration of ILC with other control techniques may give rise to better controllers that exhibit desired performance which is impossible by any individual approach.
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US$ 152.55
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a comprehensive discussion of iterative learning control (ILC) in various data dropout environments Proposes several systematic procedures for the design and analysis of ILC for stochastic systems with passive incomplete information .
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Iterative Learning Control for Systems with Iteration-Varying Trial Lengths : Synthesis and Analysis
US$ 217.40
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US$ 219.66
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Add to basketCondition: New. Print on Demand pp. 308.
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Iterative Learning Control for Systems with Iteration-Varying Trial Lengths : Synthesis and Analysis
US$ 235.30
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US$ 237.71
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Add to basketCondition: New. PRINT ON DEMAND pp. 308.
