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Adaptive filtering prediction and control /
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Englewood Cliffs, N.J. :
Prentice-Hall,
©1984.
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| Colección: | Prentice-Hall information and system sciences series.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 042 | |a dlr | ||
| 050 | 4 | |a QA402 |b .G658 1984 | |
| 082 | 0 | 4 | |a 003 |2 19 |
| 084 | |a 53.71 |2 bcl | ||
| 049 | |a UAMI | ||
| 100 | 1 | |a Goodwin, Graham C. |q (Graham Clifford), |d 1945- | |
| 245 | 1 | 0 | |a Adaptive filtering prediction and control / |c Graham C. Goodwin and Kwai Sang Sin. |
| 260 | |a Englewood Cliffs, N.J. : |b Prentice-Hall, |c ©1984. | ||
| 300 | |a 1 online resource (xii, 540 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Prentice-Hall information and system sciences series | |
| 504 | |a Includes bibliographical references (pages 516-534) and index. | ||
| 506 | |3 Use copy |f Restrictions unspecified |2 star |5 MiAaHDL | ||
| 533 | |a Electronic reproduction. |b [Place of publication not identified] : |c HathiTrust Digital Library, |d 2011. |5 MiAaHDL | ||
| 538 | |a 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. |u http://purl.oclc.org/DLF/benchrepro0212 |5 MiAaHDL | ||
| 583 | 1 | |a digitized |c 2011 |h HathiTrust Digital Library |l committed to preserve |2 pda |5 MiAaHDL | |
| 520 | |a 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. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 590 | |a Knovel |b ACADEMIC - Electronics & Semiconductors | ||
| 590 | |a Knovel |b ACADEMIC - Computer Hardware Engineering | ||
| 650 | 0 | |a Discrete-time systems. | |
| 650 | 0 | |a Filters (Mathematics) | |
| 650 | 0 | |a Prediction theory. | |
| 650 | 0 | |a Control theory. | |
| 650 | 6 | |a Systèmes échantillonnés. | |
| 650 | 6 | |a Filtres (Mathématiques) | |
| 650 | 6 | |a Théorie de la prévision. | |
| 650 | 6 | |a Théorie de la commande. | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING |x Electrical. |2 bisacsh | |
| 650 | 7 | |a Control theory |2 fast | |
| 650 | 7 | |a Discrete-time systems |2 fast | |
| 650 | 7 | |a Filters (Mathematics) |2 fast | |
| 650 | 7 | |a Prediction theory |2 fast | |
| 650 | 7 | |a Adaptives System |2 gnd | |
| 650 | 7 | |a Kontrolltheorie |2 gnd | |
| 650 | 7 | |a Stochastisches System |2 gnd | |
| 650 | 1 | 7 | |a Tijdreeksen. |2 gtt |
| 650 | 1 | 7 | |a Voorspellingen. |2 gtt |
| 650 | 1 | 7 | |a Stochastische modellen. |2 gtt |
| 650 | 1 | 7 | |a Deterministische modellen. |2 gtt |
| 650 | 7 | |a Systèmes échantillonnés. |2 ram | |
| 650 | 7 | |a Filtres (mathématiques) |2 ram | |
| 650 | 7 | |a Commande, Théorie de la. |2 ram | |
| 650 | 7 | |a Prévision, Théorie de la. |2 ram | |
| 653 | |a Complex systems |a Adaptive control systems | ||
| 700 | 1 | |a Sin, Kwai Sang, |d 1952- | |
| 776 | 0 | 8 | |i Print version: |a Goodwin, Graham C. (Graham Clifford), 1945- |t Adaptive filtering prediction and control. |d Englewood Cliffs, N.J. : Prentice-Hall, ©1984 |z 013004069X |w (DLC) 83023023 |w (OCoLC)10183440 |
| 830 | 0 | |a Prentice-Hall information and system sciences series. | |
| 856 | 4 | 0 | |u https://appknovel.uam.elogim.com/kn/resources/kpAFPC000D/toc |z Texto completo |
| 994 | |a 92 |b IZTAP | ||