Книга Iterative Learning Control for Deterministic Systems Kevin L. Moore

Iterative Learning Control for Deterministic Systems

Автор: Kevin L. Moore
Език: Английски език
Корици: С меки корици
Издател: Springer London Ltd
Наличност: Външен склад
Изпращаме след 5-8 дни
52.72 103.11 лв
Iterative Learning Control for Deterministic Systems is part of the new Advances in Industrial Contr...

Информация за книгата

Автор
Език
Английски език
Корици
Книга - С меки корици
Издадена
2011
страници
152
EAN
9781447119142
ISBN
1447119142
Enbook ID
02179415
Издател
Теглоt
272
Размери
155 x 235 x 10

Пълно описание

Iterative Learning Control for Deterministic Systems is part of the new Advances in Industrial Control series, edited by Professor M.J. Grimble and Dr. M.A. Johnson of the Industrial Control Unit, University of Strathclyde. The material presented in this book addresses the analysis and design of learning control systems. It begins with an introduction to the concept of learning control, including a comprehensive literature review. 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. Additionally, several design methods are given for LTI learning control, incorporating a technique based on parameter estimation and a one-step learning control algorithm for finite-horizon problems. Further chapters focus upon learning control for deterministic nonlinear systems, and a time-varying learning controller is presented which can be applied to a class of nonlinear systems, including the models of typical robotic manipulators. The book concludes with the application of artificial neural networks to the learning control problem. Three specific ways to neural nets for this purpose are discussed, including two methods which use backpropagation training and reinforcement learning. The appendices in the book are particularly useful because they serve as a tutorial on artificial neural networks.

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