舰船甲板运动状态预测及无人直升机着舰时刻优化OA

[Objective]In harsh sea conditions,due to the influence of wind,waves,and other factors,the ship deck is in constant motion.In such conditions,a stable and independent landing is difficult to achieve for unmanned helicopters.Generally,the operator's experience should be relied on to achieve remote control landing.This landing method is time-consuming and has great safety hazards.Therefore,it is urgent to predict the amplitude of the roll,pitch,and ascending and descending,and the motion change rate of the ship deck for determining the optimal landing time when the unmanned helicopter can land the ship safely and stably,thus reducing landing risks.[Methods]The autoregression model was employed to model and predict the motion state of the ship deck based on the time series prediction algorithm,thus predicting the optimal landing time of the unmanned helicopter.On this basis,a multi-objective optimization mathematical model was built to meet the safety requirements during the landing of the unmanned helicopter,with the simulated annealing optimization algorithm adopted to calculate the optimal landing to provide a decision-making basis for the independent landing of unmanned helicopters.Meanwhile,a ship deck motion simulator was developed to simulate the roll,pitch,ascending and descending motion of the ship deck,with an adaptive gear system built to simulate the landing process and verify the optimization results.[Results]The experimental results indicate that the predicted data curve is highly consistent with the measured data curve.The maximum error between the predicted roll and pitch values and the measured values is less than 0.01°,and the maximum error between the predicted ascending and descending values and the measured values is less than 6 mm.The maximum relative error is less than 1％,which meets the requirements for prediction accuracy.The optimization results based on the simulated annealing algorithm show that 91.50 s,96.75 s,and 99.25 s are the key moments when the roll,pitch,ascending and descending amplitudes of the ship deck and their motion change rates are small.Specifically,the comprehensive tilt angle of the deck is the lowest,and the motion change rate is the smallest at 91.50 s,which is the time for the unmanned helicopter to stably land.[Conclusions]The prediction algorithm for deck motion state based on the autoregression model features high prediction accuracy and fast response speed.Additionally,it can efficiently calculate accurate deck motion data.Compared with the traditional prediction methods,multi-objective optimization was conducted on prediction results by adopting the simulated annealing algorithm,and the selected optimal landing time can better meet the requirements for safe and stable landing of the unmanned helicopter.This study not only improves the safe landing ability of unmanned helicopters under complex motion states of ship decks,but also provides references for the take-off and landing of other types of aircraft.