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Optimized Selection Method of Air Combat Course of Action under stochastic uncertainty

Journal of Systems Science and Systems Engineering 2024年第4期33卷 494-518页

作者： Yun Zhong Jieyong Zhang Peng Sun Lujun Wan Kepeng Wang Information and Navigation College Air Force Engineering UniversityXi’an710077China Equipment Management and Unmanned Aerial Vehicle Engineering College Air Force Engineering UniversityXi’an710051China Air Traffic Control and Navigation College Air Force Engineering UniversityXi’an710051China Unit 94040 of PLA Korla841000China

Aiming at the design problem of aviation swarm combat course of action(COA),considering the influence of stochastic parameters in the causal relationship model and optimization problem model,according to the dynamic influence net(DIN)theory,stochastic simulation technique,feedforward neural network(FNN)function approximation technique and multi-objective artificial fish school algorithm(MOAFSA),this paper proposed a COA optimized method based on DIN and multi-objective stochastic chance constraint optimization for aviation swarm ***,on the basis of establishing the overall framework of the model and defining the elements of causal relationship modeling,the static and dynamic causal relationship modeling and optimization problem modeling were carried out ***,the probability propagation mechanism of DIN was established,which mainly included two aspects,i.e.,the overall process and the specific ***,input and output data were generated based on stochastic *** to these data,FNN was adopted for function approximation,and MOAFSA was adopted for iterative ***,the rationality of the model,and the effectiveness and superiority of the algorithm were verified through multiple sets of simulation cases.

关键词： stochastic uncertainty aviation swarm stochastic simulation course of action feedforward neural network multi-objective artificial fish school algorithm

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stochastic uncertain lubrication in gear transmission subjected to tribodynamic loading

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Friction 2024年第8期12卷 1741-1756页

作者： Zhou CHEN Haiming SHA Sheng LI Zheming TONG Shuiguang TONG State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China School of Mechanical Engineering Zhejiang UniversityHangzhou 310027China Wright State University 3640 Colonel Glenn HighwayDaytonOH 45435USA

A stochastic uncertain tribodynamic model is established for a spur gear pair for the first *** stochastic uncertainty of pinion rotation speed propagated to lubrication performance is *** probability density function of the minimum lubricant film thickness hmin evolves over time periodically at interval of an engagement *** between abrupt increase in meshing force and amplification of hmin uncertainty is *** and reliable lubrication performance can be achieved by suppressing the hmin uncertainty and decreasing the lubrication failure *** can be done by increasing lubricant viscosity,and decreasing input torque and uncertainty level of input rotation *** work lays a solid foundation for robust and reliability based optimization for tribodynamic gear system.

关键词： stochastic uncertainty gears elastohydrodynamic lubrication(EHL) tribodynamics

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