System Identification for Engineers : A Practical Guide to Building Accurate Models from Real Data

Language: English

Published by Alex Morgan, 2026

8398079460 / 9788398079464

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nach der Bestellung gedruckt Neuware - Printed after ordering - Most engineering models come from measurement, not derivation - even when the underlying physics is well understood. System Identification for Engineers teaches the small set of methods that cover the large majority of real identification jobs: designing an experiment that genuinely excites the dynamics you care about, cleaning and preprocessing real sensor data, fitting first- and second-order models by hand and by code, least squares and its recursive (online) form, ARX/ARMAX/Output-Error model structures, subspace state-space identification, closed-loop and nonlinear identification, and validating a model honestly before trusting it in deployment.Every method is built plain-language-first, worked through with runnable Python (NumPy, SciPy, python-control) on clearly-labeled synthetic datasets, and tied together in three full case studies that run the entire pipeline start to finish: a DC motor identified from encoder data, a quadrotor attitude axis identified under closed-loop and mild nonlinear conditions, and a battery equivalent-circuit model tracked across simulated aging.Written for working controls, robotics, and mechatronics engineers who need a model that holds up in deployment - not a research paper.…

Seller Inventory # 9788398079464

Title
System Identification for Engineers : A Practical Guide to Building Accurate Models from Real Data
Author
Alex Morgan
Publisher
Alex Morgan
Publication year
2026
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
8398079460
ISBN 13
9788398079464
Item weight
251 grams
Dimensions
229x152x9 mm

AHA-BUCH GmbH

Einbeck, Germany

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