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Identification of Physical Systems : Applications to Condition Monitoring, Fault Diagnosis, Soft Sensor and Controller Design.
Develops a systematic and a unified approach to the problem of physical system identification and its practical applications There is a need for a book which develops a systematic and a unified approach to the problem of physical system identification and its practical applications. Identification o...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken :
Wiley,
2014.
©2014 |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000Mi 4500 | ||
|---|---|---|---|
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| 050 | 4 | |a TA168 .D384 2014 | |
| 082 | 0 | 4 | |a 620.7 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Doraiswami, Rajamani. | |
| 245 | 1 | 0 | |a Identification of Physical Systems : |b Applications to Condition Monitoring, Fault Diagnosis, Soft Sensor and Controller Design. |
| 260 | |a Hoboken : |b Wiley, |c 2014. | ||
| 264 | 4 | |c ©2014 | |
| 300 | |a 1 online resource (538 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a IDENTIFICATION OF PHYSICAL SYSTEMS; Contents; Preface; Nomenclature; 1 Modeling of Signals and Systems; 1.1 Introduction; 1.2 Classification of Signals; 1.2.1 Deterministic and Random Signals; 1.2.2 Bounded and Unbounded Signal; 1.2.3 Energy and Power Signals; 1.2.4 Causal, Non-causal, and Anti-causal Signals; 1.2.5 Causal, Non-causal, and Anti-causal Systems; 1.3 Model of Systems and Signals; 1.3.1 Time-Domain Model; 1.3.2 Frequency-Domain Model; 1.4 Equivalence of Input-Output and State-Space Models; 1.4.1 State-Space and Transfer Function Model. | |
| 505 | 8 | |a 1.4.2 Time-Domain Expression for the Output Response1.4.3 State-Space and the Difference Equation Model; 1.4.4 Observer Canonical Form; 1.4.5 Characterization of the Model; 1.4.6 Stability of (Discrete-Time) Systems; 1.4.7 Minimum Phase System; 1.4.8 Pole-Zero Locations and the Output Response; 1.5 Deterministic Signals; 1.5.1 Transfer Function Model; 1.5.2 Difference Equation Model; 1.5.3 State-Space Model; 1.5.4 Expression for an Impulse Response; 1.5.5 Periodic Signal; 1.5.6 Periodic Impulse Train; 1.5.7 A Finite Duration Signal; 1.5.8 Model of a Class of All Signals. | |
| 505 | 8 | |a 1.5.9 Examples of Deterministic Signals1.6 Introduction to Random Signals; 1.6.1 Stationary Random Signal; 1.6.2 Joint PDF and Statistics of Random Signals; 1.6.3 Ergodic Process; 1.7 Model of Random Signals; 1.7.1 White Noise Process; 1.7.2 Colored Noise; 1.7.3 Model of a Random Waveform; 1.7.4 Classification of the Random Waveform; 1.7.5 Frequency Response and Pole-Zero Locations; 1.7.6 Illustrative Examples of Filters; 1.7.7 Illustrative Examples of Random Signals; 1.7.8 Pseudo Random Binary Sequence (PRBS); 1.8 Model of a System with Disturbance and Measurement Noise. | |
| 505 | 8 | |a 1.8.1 Input-Output Model of the System1.8.2 State-Space Model of the System; 1.8.3 Illustrative Examples in Integrated System Model; 1.9 Summary; References; Further Readings; 2 Characterization of Signals: Correlation and Spectral Density; 2.1 Introduction; 2.2 Definitions of Auto- and Cross-Correlation (and Covariance); 2.2.1 Properties of Correlation; 2.2.2 Normalized Correlation and Correlation Coefficient; 2.3 Spectral Density: Correlation in the Frequency Domain; 2.3.1 Z-transform of the Correlation Function; 2.3.2 Expressions for Energy and Power Spectral Densities. | |
| 505 | 8 | |a 2.4 Coherence Spectrum2.5 Illustrative Examples in Correlation and Spectral Density; 2.5.1 Deterministic Signals: Correlation and Spectral Density; 2.5.2 Random Signals: Correlation and Spectral Density; 2.6 Input-Output Correlation and Spectral Density; 2.6.1 Generation of Random Signal from White Noise; 2.6.2 Identification of Non-Parametric Model of a System; 2.6.3 Identification of a Parametric Model of a Random Signal; 2.7 Illustrative Examples: Modeling and Identification; 2.8 Summary; 2.9 Appendix; References; 3 Estimation Theory; 3.1 Overview. | |
| 500 | |a 3.2 Map Relating Measurement and the Parameter. | ||
| 520 | |a Develops a systematic and a unified approach to the problem of physical system identification and its practical applications There is a need for a book which develops a systematic and a unified approach to the problem of physical system identification and its practical applications. Identification of Physical Systems addresses this need, developing identification theory using a coherent, simple and yet rigorous approach. Starting with a least-squares method, the author develops various schemes to address the issues of accuracy, variation in the operating regimes, closed loop and inter. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Systems engineering. | |
| 650 | 0 | |a Systems engineering |x Mathematics. | |
| 650 | 6 | |a Ingénierie des systèmes. | |
| 650 | 6 | |a Ingénierie des systèmes |x Mathématiques. | |
| 650 | 7 | |a systems engineering. |2 aat | |
| 650 | 7 | |a Systems engineering |2 fast | |
| 700 | 1 | |a Stevenson, Maryhelen. | |
| 700 | 1 | |a Diduch, Chris. | |
| 776 | 0 | 8 | |i Print version: |a Doraiswami, Rajamani. |t Identification of Physical Systems : Applications to Condition Monitoring, Fault Diagnosis, Soft Sensor and Controller Design. |d Hoboken : Wiley, ©2014 |z 9781119990123 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1652084 |z Texto completo |
| 938 | |a EBL - Ebook Library |b EBLB |n EBL1652084 | ||
| 938 | |a ebrary |b EBRY |n ebr10851654 | ||
| 938 | |a ProQuest MyiLibrary Digital eBook Collection |b IDEB |n cis27828111 | ||
| 994 | |a 92 |b IZTAP | ||