Nonlinear Model Identification Methodology for Small, Fixed-Wing, Unmanned Aircraft

Abstract

This paper describes system identification of a nonlinear flight dynamic model for a small, low-cost, fixed-wing unmanned aircraft with a limited instrumentation system. Unique challenges include greater sensitivity to atmospheric disturbances and degraded data quality. Methods are presented to improve the fidelity of the identified model, including use of the vortex lattice method to supplement flight-test data and the synthesis of data from distinct flight-test maneuvers. The parameter estimation strategy is based on the time-domain formulation of the output-error method using the nonlinear flight dynamic equations for a rigid aircraft with a nonlinear aerodynamic model. Methods are presented that increase the accuracy of parameter estimates compared with standard procedures based solely on flight-test data. The paper describes a detailed application of these procedures to a particular small, fixed-wing aircraft so that they can readily be adapted to other aircraft at a similar scale.