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Автор: Kevin L. Moore Название: Iterative Learning Control for Deterministic Systems ISBN: 1447119142 ISBN-13(EAN): 9781447119142 Издательство: Springer Рейтинг: Цена: 87070.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The text follows with a complete and unifying analysis of the learning control problem for linear LTI systems using a system-theoretic approach which offers insight into the nature of the solution of the learning control problem.
Автор: Raj Madhavan; Edward Tunstel; Elena Messina Название: Performance Evaluation and Benchmarking of Intelligent Systems ISBN: 1489983007 ISBN-13(EAN): 9781489983008 Издательство: Springer Рейтинг: Цена: 144410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume examines performance evaluation and benchmarking of intelligent systems. The chapters cover a range of applications, such as assistive robotics, planetary surveying, urban search and rescue, and line tracking for automotive assembly.
Автор: Dong Shen Название: Iterative Learning Control with Passive Incomplete Information ISBN: 9811082669 ISBN-13(EAN): 9789811082665 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Поставка под заказ. Описание: 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.
Автор: Dong Shen Название: Iterative Learning Control with Passive Incomplete Information ISBN: 9811341052 ISBN-13(EAN): 9789811341052 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Поставка под заказ. Описание: 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.
Автор: Wang Danwei, Ye Yongqiang, Zhang Bin Название: Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation ISBN: 9814585599 ISBN-13(EAN): 9789814585590 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book examines iterative learning control (ILC) with a focus on design and implementation. It presents a framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between performance and stability.
Автор: Zeungnam Bien; Jian-Xin Xu Название: Iterative Learning Control ISBN: 0792382137 ISBN-13(EAN): 9780792382133 Издательство: Springer Рейтинг: Цена: 174150.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Provides a comprehensive overview of iterative learning control theory and techniques relevant to industrial automation, and focuses on research directions for the 21st century. This title examines the important aspects of this technology. It also provides coverage of ILC`s history, its real-world applications, and its robustness and convergence.
Автор: Chi Название: Data-Driven Iterative Learning Control for Discrete-Time Systems ISBN: 9811959498 ISBN-13(EAN): 9789811959493 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book belongs to the subject of control and systems theory. It studies a novel data-driven framework for the design and analysis of iterative learning control (ILC) for nonlinear discrete-time systems. A series of iterative dynamic linearization methods is discussed firstly to build a linear data mapping with respect of the system’s output and input between two consecutive iterations. On this basis, this work presents a series of data-driven ILC (DDILC) approaches with rigorous analysis. After that, this work also conducts significant extensions to the cases with incomplete data information, specified point tracking, higher order law, system constraint, nonrepetitive uncertainty, and event-triggered strategy to facilitate the real applications. The readers can learn the recent progress on DDILC for complex systems in practical 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.
Автор: David H. Owens Название: Iterative Learning Control ISBN: 144716928X ISBN-13(EAN): 9781447169284 Издательство: Springer Рейтинг: Цена: 113180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Iterative Learning Control: Background and Review. Mathematical and Linear Modelling Methodologies.- Norm Optimal Iterative Learning Control: An Optimal Control Perspective.- Predicting the Effects of Non-minimum-phase Zeros.- Predictive Norm Optimal Iterative Learning Control.- Other Applications of Norm Optimal Iterative Learning Control.- Successive Projection Algorithms.- Parameter Optimal Iterative Learning Control.- Robustness of Parameter Optimal Iterative Learning Control.- Multi-parameter Optimal Iterative Learning Control.- No Normal 0 false false false EN-GB X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name: "Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow: yes; mso-style-priority:99; mso-style-parent: ""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination: widow-orphan; font-size:11.0pt; font-family: "Calibri","sans-serif"; mso-ascii-font-family: Calibri; mso-ascii-theme-font: minor-latin; mso-hansi-font-family: Calibri; mso-hansi-theme-font: minor-latin; mso-fareast-language: EN-US;} nlinear Iterative Learning Control and Optimization.
Автор: Meng Tingting, He Wei Название: Iterative Learning Control for Flexible Structures ISBN: 9811527830 ISBN-13(EAN): 9789811527838 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Introduction.- Boundary Iterative Learning Control.- ILC for the Vibration Suppression in the Transverse Motion and Rotation.- ILC for the Nonlinearities of Differentiable and Non-Differentiable Inputs.- ILC for the Rejection of Time-Varying and Spatiotemporally Varying Disturbances.- Adaptive ILC for an Euler-Bernoulli Beam with Uncertainties.- ILC for Constant and Varying Trajectories Tracking.- ILC for a Flapping Wing Micro Aerial Vehicle.- ILC for a Flexible Two-Link Manipulator with PDE Model.- Conclusions.
Автор: Pedro Albertos; Antonio Sala Piqueras Название: Iterative Identification and Control ISBN: 1447110986 ISBN-13(EAN): 9781447110989 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.
Автор: Chris T. Freeman; Eric Rogers; Jane H. Burridge; A Название: Iterative Learning Control for Electrical Stimulation and Stroke Rehabilitation ISBN: 1447167252 ISBN-13(EAN): 9781447167259 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Iterative learning control (ILC) has its origins in the control of processes that perform a task repetitively with a view to improving accuracy from trial to trial by using information from previous executions of the task. This brief shows how a classic application of this technique – trajectory following in robots – can be extended to neurological rehabilitation after stroke. Regaining upper limb movement is an important step in a return to independence after stroke, but the prognosis for such recovery has remained poor. Rehabilitation robotics provides the opportunity for repetitive task-oriented movement practice reflecting the importance of such intense practice demonstrated by conventional therapeutic research and motor learning theory. Until now this technique has not allowed feedback from one practice repetition to influence the next, also implicated as an important factor in therapy. The authors demonstrate how ILC can be used to adjust external functional electrical stimulation of patients’ muscles while they are repeatedly performing a task in response to the known effects of stimulation in previous repetitions. As the motor nerves and muscles of the arm reaquire the ability to convert an intention to move into a motion of accurate trajectory, force and rapidity, initially intense external stimulation can now be scaled back progressively until the fullest possible independence of movement is achieved.
Автор: Wang Название: Iterative Learning Control for Equations with Fractional Derivatives and Impulses ISBN: 9811682461 ISBN-13(EAN): 9789811682469 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces iterative learning control (ILC) and its applications to the new equations such as fractional order equations, impulsive equations, delay equations, and multi-agent systems, which have not been presented in other books on conventional fields. ILC is an important branch of intelligent control, which is applicable to robotics, process control, and biological systems. The fractional version of ILC updating laws and formation control are presented in this book. ILC design for impulsive equations and inclusions are also established. The broad variety of achieved results with rigorous proofs and many numerical examples make this book unique. This book is useful for graduate students studying ILC involving fractional derivatives and impulsive conditions as well as for researchers working in pure and applied mathematics, physics, mechanics, engineering, biology, and related disciplines.
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