System Identification of a Miniature Helicopter

Abstract

Miniature helicopters provide a unique design choice for performing missions autonomously, vital to which is knowledge of a dynamic model to enable the development of control and state estimation algorithms. Toward these goals, a linear model for a miniature electric helicopter in hovering flight was identified from data obtained from a visual positioning system. Model structure determination was performed using first principles, previous work, and stepwise regression. Model parameters were computed using a two-step equation-error/output-error process in both the time and frequency domains, resulting in two complete sets of parameter estimates. Modal characteristics and predictive capability of the identified models were compared with those of a model previously identified for this aircraft using the frequency-response method.