1.

Record Nr.

UNINA9910966019703321

Autore

Jategaonkar Ravindra V

Titolo

Flight vehicle system identification : a time domain methodology / / by Ravindra V. Jategaonkar

Pubbl/distr/stampa

Reston, Va., : American Institute of Aeronautics and Astronautics, c2006

ISBN

1-60086-685-9

1-60086-466-X

1-61583-074-X

Edizione

[1st ed.]

Descrizione fisica

xviii, 534 p. : ill

Collana

Progress in astronautics and aeronautics ; ; v. 216

Disciplina

629.130113

Soggetti

Aerodynamics - Mathematical models

Aeronautics - Mathematical models

System identification

Time-domain analysis

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Cover -- Title -- Copyright -- Foreword -- Table of Contents -- Preface -- Chapter 1. Introduction -- Chapter 2. Data Gathering -- Chapter 3. Model Postulates and Simulation -- Chapter 4. Output Error Method -- Chapter 5. Filter Error Method -- Chapter 6. Equation Error Methods -- Chapter 7. Recursive Parameter Estimation -- Chapter 8. Artificial Neural Networks -- Chapter 9. Unstable Aircraft Identification -- Chapter 10. Data Compatibility Check -- Chapter 11. Model Validation -- Chapter 12. Selected Advanced Examples -- Epilogue -- Appendix A. Power Spectrum of a Multistep Input Signal -- Appendix B. Identifiability of Initial Conditions and Bias Parameters -- Appendix C. Derivation of the Likelihood Function -- Appendix D. Statistical Properties of Maximum Likelihood Estimates -- Appendix E. Minimization of Likelihood Function with Respect to Covariance Matrix R -- Appendix F. Derivation of Kalman Filter and Extended Kalman Filter -- Extended Kalman Filter -- Index.

Sommario/riassunto

Offering a systematic approach to flight vehicle system identification and covering time-domain methodology, this book addresses the



theoretical and practical aspects of various parameter estimation methods, including those in the stochastic framework.