Method for the Non‐linear Identification of Aircraft Parameters by Testing Maneuvers

Abstract

In this paper, we describe a variant of a solution for a common problem in applied statistics—we offer a variant method for estimating the parameters of a dynamic system, and observe its magnitudes, which statistically depend on the sequence of states of the system that are not observed. The method is realized by means of the multipolynomial approximations algorithm (the MPA algorithm). The method is validated by applying it to a problem of correction of finite sets of nominal experimental data on which nominal functions are constructed equationsby means of interpolation from the current states of the system. Nominal experimental data are presented on a finite set of points covering the domains of definition of the nominal functions. The nominal equations of motion of the dynamical system are defined by the nominal functions. In this paper, the concrete example of the nominal equations of motion correspond to the longitudinal motion of the aircraft similar of the F‐l6 aircraft. The nominal functions are the calculated aerodynamic characteristics. The nominal experimental data are recorded by means of experiments in a wind‐tunnel. The outcomes of measurements of the parameters of motion of the aircraft act on inputs for the MPA algorithm on a segment of real flight. The MPA algorithm defines a 32×1‐vector of estimates of parameters, which are additive corrections to the nominal experimental data.