Electronic Resource

Aircraft Aerodynamic Parameter Estimation from Flight Data Using Neural Partial Differentiation

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Penilaian

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This book presents neural partial differentiation as an estimation algorithm for extracting aerodynamic derivatives from flight data. It discusses neural modeling of the aircraft system. The neural partial differentiation approach discussed in the book helps estimate parameters with their statistical information from the noisy data. Moreover, this method avoids the need for prior information about the aircraft model parameters. The objective of the book is to extend the use of the neural partial differentiation method to the multi-input multi-output aircraft system for the online estimation of aircraft parameters from an established neural model. This approach will be relevant for the design of an adaptive flight control system. The book also discusses the estimation of aerodynamic derivatives of rigid and flexible aircraft which are treated separately. The longitudinal and lateral-directional derivatives of aircraft are estimated from flight data. Besides the aerodynamic derivatives, mode shape parameters of flexible aircraft are also identified in the book as part of identification for the state space aircraft model. Since the detailed description of the approach is illustrated through the block diagram and their results are presented in tabular form with figures of parameters converge to their estimates, the contents of this book are intended for readers who want to pursue a postgraduate and doctoral degree in science and engineering. This book is useful for practicing scientists, engineers, and teachers in the field of aerospace engineering.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
1908001449	EB0002055	629.132 3 Moh a	Central Library (OPAC)	Available

Detail Information

Series Title

SpringerBriefs in Applied Sciences and Technology

Call Number

629.132 3 Moh a

Publisher

Singapore : Springer Singapore., 2021

Collation

xi, 66p.:Ill

Language

English

ISBN/ISSN

978-981-16-0104-0

Classification

629.132 3

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

1

Subject(s)

Aerodynamics--Mathematical models

Specific Detail Info

-

Statement of Responsibility

BRF

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