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The Resource Adaptive filtering prediction and control, Graham C. Goodwin and Kwai Sang Sin

Adaptive filtering prediction and control, Graham C. Goodwin and Kwai Sang Sin

Label
Adaptive filtering prediction and control
Title
Adaptive filtering prediction and control
Statement of responsibility
Graham C. Goodwin and Kwai Sang Sin
Creator
Contributor
Subject
Language
eng
Summary
This unified survey of the theory of adaptive filtering, prediction, and control focuses on linear discrete-time systems and explores the natural extensions to nonlinear systems. In keeping with the importance of computers to practical applications, the authors emphasize discrete-time systems. Their approach summarizes the theoretical and practical aspects of a large class of adaptive algorithms. Ideal for advanced undergraduate and graduate classes, this treatment consists of two parts. The first section concerns deterministic systems, covering models, parameter estimation, and adaptive prediction and control. The second part examines stochastic systems, exploring optimal filtering and prediction, parameter estimation, adaptive filtering and prediction, and adaptive control. Extensive appendices offer a summary of relevant background material, making this volume largely self-contained. Readers will find that these theories, formulas, and applications are related to a variety of fields, including biotechnology, aerospace engineering, computer sciences, and electrical engineering
Member of
Cataloging source
OCLCE
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Prentice-Hall information and system sciences series
Adaptive filtering prediction and control, Graham C. Goodwin and Kwai Sang Sin
Label
Adaptive filtering prediction and control, Graham C. Goodwin and Kwai Sang Sin
Link
http://libproxy.rpi.edu/login?url=http://app.knovel.com/hotlink/toc/id:kpAFPC000D/adaptive-filtering-prediction
Publication
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Antecedent source
file reproduced from original
Bibliography note
Includes bibliographical references (pages 516-534) and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
black and white
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Cover; Title Page; Copyright Page; Table of Contents; Preface; 1 Introduction To Adaptive Techniques; 1.1 Filtering; 1.2 Prediction; 1.3 Control; Part I: Deterministic Systems; 2 Models for Deterministic Dynamical Systems; 2.1 Introduction; 2.2 State-Space Models; 2.2.1 General; 2.2.2 Controllable State-Space Models; 2.2.3 Observable State-Space Models; 2.2.4 Minimal State-Space Models; 2.3 Difference Operator Representations; 2.3.1 General; 2.3.2 Right Difference Operator Representations; 2.3.3 Left Difference Operator Representations; 2.3.4 Deterministic Autoregressive Moving-Average Models
  • 2.3.5 Irreducible Difference Operator Representations2.4 Models for Bilinear Systems; 3 Parameter Estimation for Deterministic Systems; 3.1 Introduction; 3.2 On-Line Estimation Schemes; 3.3 Equation Error Methods for Deterministic Systems; 3.4 Parameter Convergence; 3.4.1 The Orthogonalized Projection Algorithm; 3.4.2 The Least-Squares Algorithm; 3.4.3 The Projection Algorithm; 3.4.4 Persistent Excitation; 3.5 Output Error Methods; 3.6 Parameter Estimation with Bounded Noise; 3.7 Constrained Parameter Estimation; 3.8 Parameter Estimation for Multi-output Systems; 3.9 Concluding Remarks
  • 4 Deterministic Adaptive Prediction4.1 Introduction; 4.2 Predictor Structures; 4.2.1 Prediction with Known Models; 4.2.2 Restricted Complexity Predictors; 4.3 Adaptive Prediction; 4.3.1 Direct Adaptive Prediction; 4.3.2 Indirect Adaptive Prediction; 4.4 Concluding Remarks; 5 Control of Linear Deterministic Systems; 5.1 Introduction; 5.2 Minimum Prediction Error Controllers; 5.2.1 One-Step-Ahead Control (The SISO Case); 5.2.2 Model Reference Control (The SISO Case); 5.2.3 One-Step-Ahead Design for Multi-input Multi-output Systems; 5.2.4 Robustness Considerations
  • 5.3 Closed-Loop Pole Assignment5.3.1 Introduction; 5.3.2 The Pole Assignment Algorithm (Difference Operator Formulation); 5.3.3 Rapprochement with State- Variable Feedback; 5.3.4 Rapprochement with Minimum Prediction Error Control; 5.3.5 The Internal Model Principle; 5.3.6 Some Design Considerations; 5.4 An Illustrative Example; 6 Adaptive Control Of Linear Deterministic Systems; 6.1 Introduction; 6.2 The Key Technical Lemma; 6.3 Minimum Prediction Error Adaptive Controllers (Direct Approach); 6.3.1 One-Step-Ahead Adaptive Control (The SISO Case); 6.3.2 Model Reference Adaptive Control
  • 6.3.3 One-Step-Ahead Adaptive Controllers for Multi-input Multi-output Systems6.4 Minimum Prediction Error Adaptive Controllers (Indirect Approach); 6.5 Adaptive Algorithms for Closed-Loop Pole Assignment; 6.6 Adaptive Control of Nonlinear Systems; 6.7 Adaptive Control of Time-Varying Systems; 6.8 Some Implementation Considerations; Part II: Stochastic Systems; 7 Optimal Filtering and Prediction; 7.1 Introduction; 7.2 Stochastic State-Space Models; 7.3 Linear Optimal Filtering and Prediction; 7.3.1 The Kalman Filter; 7.3.2 Fixed-Lag Smoothing; 7.3.3 Fixed-Point Smoothing
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unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b3763801'}
Extent
1 online resource (xii, 540 pages)
Form of item
online
Isbn
9780486137728
Level of compression
  • lossless
  • lossy
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
illustrations.
Reformatting quality
  • preservation
  • access
Reproduction note
Electronic reproduction.
Specific material designation
remote
System details
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.

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