Ebook: Flight Vehicle System Identification - A Time Domain Methodology

This valuable volume offers a systematic approach to flight vehicle system identification and exhaustively covers the time domain methodology. It addresses in detail the theoretical and practical aspects of various parameter estimation methods, including those in the stochastic framework, and focuses on nonlinear models, cost functions, optimization methods, and residual analysis. A pragmatic and balanced account of pros and cons in each case is provided. The book also presents data gathering and model validation and covers both large-scale systems and high-fidelity modeling. Real-world problems dealing with a variety of flight vehicle applications are addressed and solutions are provided. Examples encompass such problems as estimation of aerodynamics, stability, and control derivatives from flight data, flight path reconstruction, nonlinearities in control surface effectiveness, stall hysteresis, unstable aircraft, and other critical considerations. Beginners, as well as practicing researchers, engineers, and working professionals who wish to refresh or broaden their knowledge of flight vehicle system identification, will find this book highly beneficial. Based on years of experience, the author also provides recommendations for overcoming problems likely to be faced in developing complex nonlinear and high-fidelity models, and the book can help the novice negotiate the challenges of developing highly accurate mathematical models and aerodynamic databases from experimental flight data.
- Data and information appearing in this book are for informational purposes only. AIAA and the author are not responsible for any injury or damage resulting from use or reliance, nor do AIAA and the author warrant that use or reliance will be free from privately owned rights.
Content:
Front Matter
• Interactive Graphs Table  (143) • Preface
• Table of Contents
1. Introduction
2. Data Gathering
3. Model Postulates and Simulation
4. Output Error Method
5. Filter Error Method
6. Equation Error Methods
7. Recursive Parameter Estimation
8. Artificial Neural Networks
9. Unstable Aircraft Identification
10. Data Compatibility Check
11. Model Validation
12. Selected Advanced Examples
Epilogue
Appendices
Index