Vee-tail conceptual design criteria for commercial transport aeroplanes

Vee-tail configuration is an unconventional tail configuration for commercial transport aviation, the use of which could suppose reductions on CO2 emissions. The conceptual design criteria have been selected inspired on the certification requirements established by the aviation regulation in force. They are static stability in cruise, control after Critical Engine Failure(CEF),control in crosswind landing, and trim in these three conditions. The study is carried out through a combination of semi-empirical techniques and Vortex-Lattice Methods(VLM) and thus this analyses the consequences of applying these criteria to a reference aeroplane substituting its conventional tail by a parametrised Vee-tail configuration. The Vee-tail is defined by four parameters:span, root chord, taper ratio and dihedral angle. The results of the study establish a relation between the parameters in order to accomplish the proposed conceptual design criteria. To sum up, minimum and maximum limits are obtained for dihedral angle depending on the combination of the rest of parameters. In addition, a design restriction to the yawing trailing-edge tail control is reached when the results are analysed, demonstrating that its minimum size must be between 60%and 80% of the half-span of the tail, depending on the Vee-tail geometry.

Data fusion and simulation-based planning and control in cyber physical system for digital assembly of aeroplane

This paper introduces a CPS application for intelligent aeroplane assembly.At first,the CPS structure is presented,which acquires the characteristics of general CPS and enables“simulation-based planning and control”to achieve high level intelligent assembly.Then the paper puts forward data fusion estimation algorithm under synchronous and asynchronous sampling,respectively.The experiment shows that global optimal distributed fusion estimation under synchronized sampling proves to be closer to the actual value compared with ordinary weighted estimation,and multi-scale distributed fusion estimation algorithm of wavelet under asynchronous sampling does not need time registration,it can also directly link to data,and the error is smaller.This paper presents hybrid control strategy under the circumstance of joint action of the inner and outer loop to address the problems caused by the less controllable feature of the parallel mechanism when undertaking online process simulation and control.A robust adaptive sliding mode controller is designed based on disturbance observer to restrain inner interference and maintain robustness.At the same time,an outer collaborative trajectory planning is also designed.All the experiment results show the feasibility of above proposed methods.

Energy-optimal trajectory planning for solar-powered aircraft using soft actor-critic

High-Altitude Long-Endurance(HALE)solar-powered Unmanned Aircraft Vehicles(UAVs)can utilize solar energy as power source and maintain extremely long cruise endurance,which has attracted extensive attentions from researchers.Trajectory optimization is a promising way to achieve superior flight time because of the finite solar energy absorbed in a day.In this work,a method of trajectory optimization and guidance for HALE solar-powered aircraft based on a Reinforcement Learning(RL)framework is introduced.According to flight and environment information,a neural network controller outputs commands of thrust,attack angle,and bank angle to realize an autonomous flight based on energy maximization.The validity of the proposed method was evaluated in a 5-km radius area in simulation,and results have shown that after one day-night cycle,the battery energy of the RL-controller was improved by 31%and 17%compared with those of a Steady-State(SS)strategy with a constant speed and a constant altitude and a kind of statemachine strategy,respectively.In addition,results of an uninterrupted flight test have shown that the endurance of the RL controller was longer than those of the control cases.