敏感器故障诊断与容错控制一体化设计

摘要： 针对卫星敏感器故障情况下的故障诊断与容错控制一体化设计问题,本文将敏感器有效性因子和控制器增益作为整体,利用区域极点配置方法设计综合输出反馈控制律,保证了良好的系统性能;再利用敏感器偏差的最优估计方法进行实时估计敏感器有效性因子,反解即可得到控制器增益,保证了控制的实时性和快速性;最后通过仿真验证了所提方法的有效性.     

Epistemic uncertainty quantification in flutter analysis using evidence theory

Aimed at evaluating the structural stability and flutter risk of the system, this paper manages to quantify epistemic uncertainty in flutter analysis using evidence theory, including both parametric uncertainty and method selection uncertainty, on the basis of information from limited experimental data of uncertain parameters. Two uncertain variables of the actuator coupling system with unknown probability distributions, that is bending and torsional stiffness, which are both described with multiple intervals and the basic belief assignment(BBA) extricated from the modal test of actuator coupling systems, are taken into account. Considering the difference in dealing with experimental data by different persons and the reliability of various information sources, a new combination rule of evidence––the generalized lower triangular matrices method is formed to acquire the combined BBA. Finally the parametric uncertainty and the epistemic uncertainty of flutter analysis method selection are considered in the same system to realize quantification. A typical rudder of missile is selected to examine the present method, and the dangerous range of velocity as well as relevant belief and plausibility functions is obtained. The results suggest that the present method is effective in obtaining the lower and upper bounds of flutter probability and assessing flutter risk of structures with limited experimental data of uncertain parameters and the belief of different methods.     

基于MODPSO-GSA的协同空战武器目标分配

提出基于多目标决策理论的协同空战武器目标分配模型,并用进化多目标优化算法求解.空战是一个多阶段攻防过程,针对多数空战武器目标分配采用一次性完全分配、不考虑火力资源消耗等不足,构建多目标决策模型,在达到毁伤门限的前提下,同时对一次攻击后使敌编队的总期望剩余威胁最小和分配导弹消耗量最小两个目标函数寻优.提出用多目标离散粒子群-引力搜索算法(MODPSO-GSA)求解分配模型,该混合进化多目标优化算法结合二者优点,具有稳定的全局搜索能力并保证收敛到Pareto前沿.该算法可求得满足毁伤门限的不同耗弹量的分配方案最优解集以供指挥员决策参考.仿真算例验证了新模型及所提出MODPSO-GSA进化多目标优化求解算法的有效性.      

多无人机系统协同多任务分配模型与仿真

针对多约束条件下的多无人机系统协同多任务分配问题(CMTAP),提出了利用多约束条件下的多车场车辆路径问题(MDVRPMC)对协同多任务分配问题进行建模,在设计基于Pareto最优的遗传模拟退火算法的基础上,对存在任务点动态时间窗口约束、任务类型约束、无人机任务能力约束等条件下的协同多任务分配问题进行了求解.实例仿真表...