System Identification of a Miniature Electric Helicopter using MEMS Inertial, Optic Flow and Sonar Sensing

Knowledge of a linearized dynamic model for a given vehicle greatly aids the development of observers for state estimation and controllers for automation, however a linearized model consists of stability derivatives that can be difficult to obtain from first-principles modeling. This paper presents the identification of a linearized model of a small electric helicopter about the hovering flight condition using the input and output time histories and benchtop testing. On-board orientation sensing is provided using 6DOF inertial measurement. Translational motion estimation is obtained using optic flow-based visual sensors and a sonar altitude ranging sensor. The methodology and results of the estimation are presented.