Semi-empirical estimation and experimental method for determining inertial properties of the Unmanned Aerial System – UAS-S4 of Hydra Technologies

Abstract

This article presents a structural analysis of the Unmanned Aerial System UAS-S4 ETHECATL. Mass, centre of gravity position and principal mass moment of inertia are numerically determined and further experimentally verified using the ‘pendulum method’. The numerical estimations are computed through Raymer and DATCOM statistical-empirical methods coupled with mechanical calculations. The mass of the UAS-S4 parts are estimated according to their sizes and the UAS-S4 class, by the means of Raymer statistical equations. The UAS-S4 is also decomposed in several simple geometrical figures which centres of gravity are individually computed, weighted and then arithmetically averaged to find the whole UAS-S4 centre of gravity. In the same way, DATCOM equations allows us to estimate the mass moments of inertia of each UAS-S4 parts that are finally sum up according to the Huygens-Steiner theorem for computing the principal moment of inertia of the whole UAS-S4. The mass of de UAS-S4 is experimentally determined with two scales. Its centre of gravity coordinates and its mass moment of inertia are found using the pendulum method. A bifilar torsion-type pendulum methodology is used for the vertical axis(14)and a simple pendulum methodology is used for the longitudinal and transversal axes(12). The test object is installed on a pendulum (simple or bifilar torsion pendulum) which is led to oscillate freely while recording the oscillation's angles and speed, by the means of three sensors (an accelerometer, a gyroscope and a magnetometer) that the calibration is also discussed. Simultaneously, nonlinear dynamic models are developed for the rotational motion of pendulums, including the effects of large-angle oscillations, aerodynamic drag, viscous damping and additional momentum of air. ‘Algorithms of minimization’ are then used to simulate and actualise the dynamic models and finally chose the model that simulated data best fit the experimentally recorded one. Pendulum parameters, such as mass moment of inertia, are lastly extracted from the chosen model. To determine the accuracy of the nonlinear dynamics approach of the pendulum method, the experimental results for an object of uniform density for which the mass moments of inertia are computed numerically from geometrical data are presented along with the experimental results obtained for the UAS-S4 ETHECATL. For the uniform density object, the experimental method gives, with respect to the numerical results, an error of 4.4% for the mass moment of inertia around theZaxis and 9.5% for the moment of inertia around theXandYaxes. In addition, the experimental results for the UAS-S4 inertial values validate the numerical calculation through DATCOM method with a relative error of 6.52% on average.

Lyapunov-based Robust Adaptive Configuration of the UAS-S4 Flight Dynamics Fuzzy Controller

“…The second sub-model (propulsion) was built using a two-stroke engine integration model relying on the operation of an internal combustion engine (Otto Cycle), and on the propeller analysis (Blade Element Theory) [29, 30]. Raymer and DATCOM techniques were used to implement the third sub-model (mass and inertia) [31]. Finally, the fourth sub-model (a control surface actuation system) was designed using the servomotors’ characteristics, and the final UAS-S4 model was obtained by the sub-models integration [3].…”

Research on the Measurement Technology of Rotational Inertia of Rigid Body Based on the Principles of Monocular Vision and Torsion Pendulum

“…For example, rotational inertia is crucial in various applications, such as gyroscopes [ 8 ], celestial bodies [ 9 ], and motor rotors [ 10 ]. Furthermore, a rotational inertia test is required for all equipment with rotational behavior, such as spacecrafts [ 11 ], aircrafts [ 12 ], automobiles [ 13 ], robots [ 14 ], specialized helmets [ 15 ], and tennis rackets [ 16 ].…”

Structural Sizing and Topology Optimization Based on Weight Minimization of a Variable Tapered Span-Morphing Wing for Aerodynamic Performance Improvements

“…The LARCASE team developed sophisticated methodologies for predicting the aerodynamic behavior and performance of the unmanned aerial systems UAS-S4 and UAS-S45 of Hydra Technologies [22][23][24]. This work concentrated on the structural analysis and optimization of unmanned aerial systems UAS-S4 and UAS-S45 based on CFD optimization results (aerodynamic performance, viscous damping and oscillations) [25,26]. The aerodynamic lift distribution over a wing's entire surface was calculated using a numerical analysis based on the XFLR5 code results [27].…”

“…Figure25. Element density plots with the iteration number for moving wing: (A) leading edge of rib 1, (B) trailing edge of rib 1, (C) support stringer of a front spar, and (D) support stringer of a rear spar.…”