By Arun K. Tangirala
ISBN-10: 1439895996
ISBN-13: 9781439895993
Master innovations and effectively construct types utilizing a unmarried Resource
Vital to all data-driven or measurement-based technique operations, process id is an interface that's in accordance with observational technology, and facilities on constructing mathematical versions from saw information. Principles of process identity: concept and Practice is an introductory-level ebook that provides the fundamental foundations and underlying equipment proper to procedure id. the final scope of the booklet specializes in approach id with an emphasis on perform, and concentrates so much in particular on discrete-time linear method identification.
Useful for either idea and Practice
The ebook provides the foundational pillars of id, particularly, the speculation of discrete-time LTI platforms, the fundamentals of sign processing, the speculation of random strategies, and estimation concept. It explains the middle theoretical ideas of creating (linear) dynamic types from experimental facts, in addition to the experimental and functional points of identity. the writer deals glimpses of recent advancements during this region, and offers numerical and simulation-based examples, case reviews, end-of-chapter difficulties, and different abundant references to code for representation and training.
Comprising 26 chapters, and perfect for coursework and self-study, this vast textual content:
- Provides the basic ideas of identification
- Lays down the principles of mathematical descriptions of platforms, random methods, and estimation within the context of identification
- Discusses the speculation concerning non-parametric and parametric versions for deterministic-plus-stochastic LTI platforms in detail
- Demonstrates the suggestions and techniques of id on assorted case-studies
- Presents a steady improvement of state-space id and grey-box modeling
- Offers an summary of complex themes of identity specifically the linear time-varying (LTV), non-linear, and closed-loop identification
- Discusses a multivariable method of identity utilizing the iterative central part analysis
- Embeds MATLAB® codes for illustrated examples within the textual content on the respective points
Principles of approach identity: thought and Practice
provides a proper base in LTI deterministic and stochastic structures modeling and estimation idea; it's a one-stop reference for introductory to reasonably complicated classes on approach id, in addition to introductory classes on stochastic sign processing or time-series analysis.The MATLAB scripts and SIMULINK versions used as examples and case experiences within the publication also are on hand at the author's site: http://arunkt.wix.com/homepage#!textbook/c397
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Additional info for Principles of System Identification: Theory and Practice
Sample text
2 depicts the applications of models to four major branches of process systems engineering, namely, design, estimation (prediction), control and monitoring. Central to all these applications is the use of models in simulations and predictions, which constitute the key incentives of model development. Simulations, by their computational nature, offer a cost and time-effective, safe alternative to experiments that are usually time-consuming, expensive and marked with safety issues. Significant advances in the fields of computational science and technology have rendered simulations as powerful ways of understanding processes, bringing about innovations and testing new designs and strategies.
1 Indices of non-zero coefficients in the generating polynomial of full-length PRBS ........... 1 Settings for the two-tank system simulation ........................................................................ 1 Results from IPCA and PCA of flow mixing data ............................................................... 809 xxxiii This page intentionally left blank PART I I NTRODUCTION M ODELS FOR S YSTEMS TO I DENTIFICATION AND L INEAR D ETERMINISTIC 1 Introduction This chapter introduces the basic concepts of identification and provides an overview of the subject.
12. 341 Plot of 95% confidence intervals (for mean) from 1000 realizations; 51 of these intervals do not contain the true mean µ0 = 0. 6 Snapshot of the input-output data used in estimation of the ARX model. 2. 2. 362 Predictions vs. measurements. 5, obtained from 200 realizations. 7. 2. 1. 2 for whiteness. 432 Rectangular window function and its Fourier transform magnitude. 437 Illustration of spectral leakage of sine wave. 5 xxx List of Figures (SEE COLOR INSERT) Window functions and the magnitudes of their Fourier transforms.
Principles of System Identification: Theory and Practice by Arun K. Tangirala
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