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Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems

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Description:This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Considering iterative learning control (ILC) in the iteration domain, a unified analysis and design framework is presented that enables designers to consider both robustness and monotonic convergence for typical uncertainty models. Topics include: Conversion of the ILC system, which has dynamics in both the time and iteration domains, into the supervector framework, with dynamics only in the iteration domain.- Development of iteration-domain uncertainty models in the supervector framework.- ILC design for monotonic convergence for plant subject to parametric interval uncertainty in the Markov matrix.- Algebraic H-infinity design for ILC for plant subject to iteration-domain frequency uncertainty.- Kalman-filter-based ILC algorithms for plant subject to iteration-domain stochastic uncertainties.- Analytical determination of the base-line error of ILC algorithms.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems. To get started finding Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems, you are right to find our website which has a comprehensive collection of manuals listed.
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Pages: 230

Format: PDF, EPUB & Kindle Edition

Publisher: Springer London

Release: 2010

ISBN: 1280944250

Description: This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Considering iterative learning control (ILC) in the iteration domain, a unified analysis and design framework is presented that enables designers to consider both robustness and monotonic convergence for typical uncertainty models. Topics include: Conversion of the ILC system, which has dynamics in both the time and iteration domains, into the supervector framework, with dynamics only in the iteration domain.- Development of iteration-domain uncertainty models in the supervector framework.- ILC design for monotonic convergence for plant subject to parametric interval uncertainty in the Markov matrix.- Algebraic H-infinity design for ILC for plant subject to iteration-domain frequency uncertainty.- Kalman-filter-based ILC algorithms for plant subject to iteration-domain stochastic uncertainties.- Analytical determination of the base-line error of ILC algorithms.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems. To get started finding Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems

Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems

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