An improved online system identification method for tiltrotor aircraft

Abstract

Abstract An online system identification method for tiltrotor aircraft flight dynamics modeling is developed in this paper. A general parametric flight dynamics model which can be used for online identification purpose in the three flight modes of tiltrotor aircraft (i.e., helicopter mode, conversion mode, and fixed-wing mode) is developed, and an unideal noise model is also introduced in order to minimize the parameter identification error caused by measurement noise. An adaptive model structure identification algorithm is established by introducing local accuracy criteria, so that a time variant optimal model structure is obtained in real time. A weighted recursive least squares algorithm is established for parameter identification, and a time variant weighting matrix is designed to provide best numerical performance in the identification procedure at any time. A comprehensive nonlinear flight dynamics model of a notional tiltrotor aircraft is used to generate simulation flight test data in all flight modes, and the identification results of the notional tiltrotor aircraft in fixed wing mode, helicopter model as well as conversion mode are obtained and verified. Finally, the flight dynamics model of an unmanned tiltrotor aircraft in helicopter mode is identified by using the real flight test data. The identification results show that the online system identification method for tiltrotor aircraft developed in this paper is effective, efficient and robust.