This book provides a comprehensive overview of both the theoretical underpinnings and the practical application of aircraft modeling based on experimental data - also known as aircraft system identification. Much of the material presented comes from the authors' own extensive research and teaching a
Principles of System Identification: Theory and Practice
✍ Scribed by Tangirala, Arun K
- Publisher
- CRC Press
- Year
- 2014
- Tongue
- English
- Leaves
- 881
- Category
- Library
No coin nor oath required. For personal study only.
✦ Table of Contents
Content: Introduction --
A journey into identification --
Mathematical descriptions of processes: models --
Models for discrete-time LTI systems --
Transform-domain models for linear Time-invariant systems --
Sampling and discretization --
Random processes --
Time-domain analysis: correlation functions --
Models for linear stationary processes --
Fourier analysis and spectral analysis of deterministic signals --
Spectral representations of random processes --
Introduction to estimation --
Goodness of estimators --
Estimation methods: part I --
Estimation methods: part II --
Estimation of signal properties --
Non-parametric and parametric models for identification --
Predictions --
Identification of parametric time-series models --
Identification of non-parametric input-output models --
Identification of parametric input-output models --
Statistical and practical elements of model building --
Identification of state-space models --
Case studies --
Advanced topics in SISO identification --
Linear multivariable identification
✦ Subjects
Автоматизация;Теория автоматического управления (ТАУ);Книги на иностранных языках;
📜 SIMILAR VOLUMES
<p><p>This book is a continuation of our recently published book “Algebraic formalization of smart systems. Theory and practice.” It incorporates a new concept of quasi-fractal algebraic systems, based on A.I. Maltsev’s theory of algebraic systems and the theory of fractals developed by Benoit Mande
Methods of recursive identification deal with the problem of building mathematical models of signals and systems on-line, at the same time as data is being collected. Such methods, which are also known as adaptive algorithms or sequential parameter estimation methods, may be applied to a wide spectr