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Iterative Learning Control for Deterministic Systems, Kevin L. Moore


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Цена: 13060.00р.
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Автор: Kevin L. Moore
Название:  Iterative Learning Control for Deterministic Systems
ISBN: 9781447119142
Издательство: Springer
Классификация:





ISBN-10: 1447119142
Обложка/Формат: Soft cover
Страницы: 152
Вес: 0.27 кг.
Дата издания: 12.12.2011
Серия: Advances in Industrial Control
Язык: English
Издание: Softcover reprint of
Иллюстрации: Xvi, 152 p.
Размер: 234 x 156 x 9
Читательская аудитория: Professional & vocational
Основная тема: Manufacturing, Machines, Tools
Ссылка на Издательство: Link
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Поставляется из: Германии
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.


Deterministic Solvers for the Boltzmann Transport Equation

Автор: Sung-Min Hong; Anh-Tuan Pham; Christoph Jungemann
Название: Deterministic Solvers for the Boltzmann Transport Equation
ISBN: 3709111196 ISBN-13(EAN): 9783709111192
Издательство: Springer
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Цена: 21661.00 р.
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Описание: This book, the first comprehensive description of the numerical methods, covers every aspect of the Boltzmann transport equation, including transport in bulk and in inversion layers. It analyzes the issues of stabilization and band structure mapping in detail.

Iterative Learning Control for Electrical Stimulation and Stroke Rehabilitation

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
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Цена: 7685.00 р.
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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.


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