High-order iterative learning identification of projectile's aerodynamic drag coefficient curve from radar measured velocity data

Abstract

Extracting projectile's optimal fitting drag coefficient curve C df C df C df from radar measured velocity data is considered as an optimal tracking control problem (OTCP) where C df C df C df is regarded as a virtual control function while the radar measured velocity data are taken as the desired output trajectory to be optimally tracked. With a three-degree of freedom (DOF) point mass trajectory prediction model, a high-order iterative learning identification scheme with time varying learning gains is proposed to solve this OTCP with a minimax performance index and an arbitrarily chosen initial control function. The convergence of the high-order iterative learning identification is analyzed and a guideline to choose the time varying learning gains is given. The curve identification results from a set of actual flight testing data are compared and discussed for different learning gains. These results demonstrate that the high-order iterative learning identification is effective and applicable to practical curve identification problems.

Identification of the Time-Varying Ventricular Parameters During the Ejection Phase of the Cardiac Cycle: The Martingale Optimality Principle Approach

“…(4) The time-varying coefficients could be treated as unknown controllers to be estimated to track the observed data. The method of Pontryagin maximum principle could be used to find the desired values [5,23]. In this report we introduce another method that is based on the stochastic and the martingale optimality principle [13,14,24,25].…”

Bulletin of the Polish Academy of Sciences: Technical Sciences

“…The basic problem in developing such models is the ability to determine the coefficients of aerodynamic forces and moments that appear in the model. There are many methods for those coefficients estimation but the most accurate are indirect methods based on the measurement of the projectile flight parameters [1][2][3][4][5][6][7][8][9]. In [5] cubic splines with deficiency number 2 (cubic splines with continuous first derivatives [10]) are used in order to parametrize the drag coefficient curve.…”