Proceedings of the 21st IEEE Conference on Decision & Control PDF Download
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Author:
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 556
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Book Description
Author: Hyo-Sung Ahn
Publisher: Springer Science & Business Media
ISBN: 1846288592
Category : Technology & Engineering
Languages : en
Pages : 237
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Book Description
This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. It presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty. The book shows how to use robust iterative learning control in the face of model uncertainty.
Author:
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 556
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Book Description
Author: IEEE Control Systems Society
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 1120
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Book Description
Author:
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 450
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Book Description
Author:
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 904
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Book Description
Author: IEEE Control Systems Society
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
ISBN: 9780780308725
Category : Technology & Engineering
Languages : en
Pages : 954
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Book Description
Author:
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 726
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Book Description
Author: IEEE Control Systems Society
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 1238
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Book Description
Author: Somayeh Sojoudi
Publisher: Springer Science & Business Media
ISBN: 1441915494
Category : Technology & Engineering
Languages : en
Pages : 197
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Book Description
Structurally Constrained Controllers: Analysis and Synthesis studies the control of interconnected systems with a particular application in network, power systems, flight formations, etc. It introduces four important problems regarding the control of such systems and then proposes proper techniques for solving them.
Author: Allamaraju Subrahmanyam
Publisher: CRC Press
ISBN: 1000732908
Category : Technology & Engineering
Languages : en
Pages : 94
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Book Description
Models of dynamical systems are required for various purposes in the field of systems and control. The models are handled either in discrete time (DT) or in continuous time (CT). Physical systems give rise to models only in CT because they are based on physical laws which are invariably in CT. In system identification, indirect methods provide DT models which are then converted into CT. Methods of directly identifying CT models are preferred to the indirect methods for various reasons. The direct methods involve a primary stage of signal processing, followed by a secondary stage of parameter estimation. In the primary stage, the measured signals are processed by a general linear dynamic operation—computational or realized through prefilters, to preserve the system parameters in their native CT form—and the literature is rich on this aspect. In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation. In this book, the authors provide an overview of CT system identification, consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system identification, bring them into mainstream model parameterization via basis functions, present a methodology to robustify the recursive least squares algorithm for parameter estimation of linear regression models, suggest a simple off-line error quantification scheme to show that it is possible to quantify error even in the absence of informative priors, and indicate some directions for further research. This modest volume is intended to be a useful addition to the literature on identifying CT systems.
