Drag coefficient curve identification of projectiles from flight tests via optimal dynamic fitting

Extracting:a projectile's optimally fitting drag coefficient curve C-df(M) from flight testing data is considered as an optimal tracking control problem (OTCP), where C-df(M) is regarded as the control profile, while the flight testing data is the desired trajectory to be optimally tracked. Cubic splines with deficiency number 2, which can guarantee the continuity and fitting flexibility of C-df(M); are employed to parametrize the C-df(M). This functional minimization problem (OTCP) can then be converted into a multivariable parametric minimization one. The standard Newton-Raphson iteration is formulated. A quasi-Newton-Raphson iterative scheme is proposed to reduce the cost of computation by half, and performs a near-second-order convergence by using the first-order gradient only. A further simplification is proposed by using the approximated Hamiltonian function, which cuts the computing cost by half once more. A practical testing data-reduction result is presented to show that the optimal dynamic fitting is a useful scheme for aerodynamic coefficient curve identification. Copyright (C) 1997 Elsevier Science Ltd.