Aircraft Aerodynamic Parameter Estimation from Flight Data Using Neural Partial Differentiation (Record no. 75371)

000 -LEADER
fixed length control field 04152nam a22005775i 4500
001 - CONTROL NUMBER
control field 978-981-16-0104-0
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801213609.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210223s2021 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789811601040
-- 978-981-16-0104-0
082 04 - CLASSIFICATION NUMBER
Call Number 629.1
100 1# - AUTHOR NAME
Author Mohamed, Majeed.
245 10 - TITLE STATEMENT
Title Aircraft Aerodynamic Parameter Estimation from Flight Data Using Neural Partial Differentiation
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2021.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XI, 66 p. 32 illus. in color.
490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Applied Sciences and Technology,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Aircraft System Identification -- Neural Modeling and Parameter Estimation -- Identification of Aircraft Longitudinal Derivatives -- Identification of Aircraft Lateral-directional Derivatives -- Identification of a Flexible Aircraft Derivatives -- Conclusions and Future Work -- Appendix A: Neural Network Based Solution of Ordinary Differential Equation -- Appendix B: Output Error Method. .
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Dongare, Vikalp.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-981-16-0104-0
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2021.
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-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Aerospace engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Astronautics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Automotive engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical models.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Aerospace Technology and Astronautics.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Automotive Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical Modeling and Industrial Mathematics.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2191-5318
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-- ZDB-2-ENG
912 ## -
-- ZDB-2-SXE

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