Dynamics Modeling and Pitching Parameters Identification of a Novel Hybrid UAV

Abstract

Unmanned Aerial Vehicle (UAV) is an appealing topic for aeronautical researchers due to its tremendous application in the world. To make controller design possible for a novel UAV design, dynamics modeling-a process of deriving a set of differential equations governing the motion of the aircraft-is essential. In this paper, we present a conceptual approach to obtain the parameterized dynamics equation based on application of Newton's second law and approximations of aerodynamics effects on the UAV. From there, two identification methods are introduced, one bases on maximum likelihood while the other employs linear regression to estimate the aircraft's dynamic parameters such as aerodynamic and control and stability derivatives through an example involving our new hybrid UAV developed from fixed wing aircraft and a tricopter. Wind tunnel tests for a one-third scaled model are carried out to receive outputs of the model, such as Euler angles and rotation rates, from prescribed input signals, which are rotors' speeds, then pitching parameters are identified. Estimated model would then be validated to another set of experiment to show the fitness, hence remarks regarding the accuracy of the dynamics model and the parameters themselves can be made. The articles show that for the derived mathematical model, the estimation results were well fitted, and cross-validation also indicates that the model was fine enough. The methods have strong implications about its generality that is applicable to other novel vehicle designs.