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 focusing 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.17Maine, R. E. and Iliff, K. W., aquot;Usera#39;s Manual for MMLE3, a General FORTRAN Program for Maximum Likelihood Parameter Estimation, aquot; NASA TP-1563, Nov. 1980. l8Vaughan, D. R., aquot;A Nonrecursive Algebraic Solution for the Discrete Riccatianbsp;...
|Title||:||Flight vehicle system identification|
|Author||:||Ravindra V. Jategaonkar|
|Publisher||:||Amer Inst of Aeronautics & - 2006|