Energy Model for UAV Communications:Experimental Validation and Model Generalization

Wireless communication involving unmanned aerial vehicles(UAVs)is expected to play an important role in future wireless networks.However,different from conventional terrestrial communication systems,UAVs typically have rather limited onboard energy on one hand,and require additional flying energy consumption on the other hand.This renders energy-efficient UAV communication with smart energy expenditure of paramount importance.In this paper,via extensive flight experiments,we aim to firstly validate the recently derived theoretical energy model for rotary-wing UAVs,and then develop a general model for those complicated flight scenarios where rigorous theoretical model derivation is quite challenging,if not impossible.Specifically,we first investigate how UAV power consumption varies with its flying speed for the simplest straight-and-level flight.With about 12,000 valid power-speed data points collected,we first apply the model-based curve fitting to obtain the modelling parameters based on the theoretical closed-form energy model in the existing literature.In addition,in order to exclude the potential bias caused by the theoretical energy model,the obtained measurement data is also trained using a model-free deep neural network.It is found that the obtained curve from both methods can match quite well with the theoretical energy model.Next,we further extend the study to arbitrary 2-dimensional(2-D)flight,where,to our best knowledge,no rigorous theoretical derivation is available for the closed-form energy model as a function of its flying speed,direction,and acceleration.To fill the gap,we first propose a heuristic energy model for these more complicated cases,and then provide experimental validation based on the measurement results for circular level flight.

Autonomous flight control with different strategies applied during the complete flight cycle for flapping-wing flying robots

Flapping-wing flying robots(FWFRs),especially large-scale robots,have unique advantages in flight efficiency,load capacity,and bionic hiding.Therefore,they have significant potential in environmental detection,disaster rescue,and anti-terrorism explosion monitoring.However,at present,most FWFRs are operated manually.Some have a certain autonomous ability limited to the cruise stage but not the complete flight cycle.These factors make an FWFR unable to give full play to the advantages of flapping-wing flight to perform autonomous flight tasks.This paper proposed an autonomous flight control method for FWFRs covering the complete process,including the takeoff,cruise,and landing stages.First,the flight characteristics of the mechanical structure of the robot are analyzed.Then,dedicated control strategies are designed following the different control requirements of the defined stages.Furthermore,a hybrid control law is presented by combining different control strategies and objectives.Finally,the proposed method and system are validated through outdoor flight experiments of the HIT-Hawk with a wingspan of 2.3 m,in which the control algorithm is integrated with an onboard embedded controller.The experimental results show that this robot can fly autonomously during the complete flight cycle.The mean value and root mean square(RMS)of the control error are less than 0.8409 and 3.054 m,respectively,when it flies around a circle in an annular area with a radius of 25 m and a width of 10 m.

Experimentation on Leader-Following Formation for Fixed-Wing UAVs

Fixed-wing unmanned aerial vehicles(UAVs)are a primary focus of current UAV research.Challenges arise in theirflight due to high speed and complex maneuverability.This paper explores the coordinated turn guidance law for fixed-wing UAVs and validates an experimental leader-follower formation platform inflight.Results demonstrate the effectiveness of the proposed algorithm and platform in enabling actual leader-follower formationflights for fixed-wing UAVs.

Transition prediction and sensitivity analysis for a natural laminar flow wing glove flight experiment

Natural laminar flow technology can significantly reduce aircraft aerodynamic drag and has excellent technical appeal for transport aircraft development with high aerodynamic efficiency.Accurately and efficiently predicting the laminar-to-turbulent transition and revealing the maintenance mechanism of laminar flow in a transport aircraft’s flight environment are significant for developing natural laminar flow wings.In this research,we carry out natural laminar flow flight experiments with different Reynolds numbers and angles of attack.The critical N-factor is calibrated as 9.0 using flight experimental data and linear stability theory from a statistical perspective,which makes sure that the relative error of transition location is within 5%.We then implement a simplified e^(N) transition prediction method with a similar accuracy compared with linear stability theory.We compute the sensitivity information for the simplified eN method with an adjointbased method,using the automatic differentiation technique(ADjoint).The impact of Reynolds numbers and pressure distributions on TS waves is analyzed using the sensitivity information.Through the sensitivity analysis,we find that:favorable pressure gradients not only suppress the development of TS waves but also decrease their sensitivity to Reynolds numbers;there exist three special regions which are very sensitive to the pressure distribution,and the sensitivity decreases as the local favorable pressure gradient increases.The proposed sensitivity analysis method enables robust natural laminar flow wings design.