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不确定环境下多UCAV实时任务规划方法研究

Study on the Real-Time Task Planning of Multi-UCAN in Uncertain Environment

【作者】 唐婷

【导师】 陈侠;

【作者基本信息】 沈阳航空航天大学 , 模式识别与智能系统, 2012, 硕士

【摘要】 由于无人作战飞机(Unmanned Combat Aerial Vehicle, UCAV)能够完成各种复杂的作战任务,在现代战争中发挥的作用越来越显著,因而受到各国军事高层的关注。在实际的战场环境中,存在着战场环境的多变性、情报获取的不确定性和武器作战效能的随机性等不确定因素,因此研究不确定环境下多UCAV任务规划方法问题已成为一个新的重要研究课题,而任务分配又是多UCAV任务规划系统的基础和保障,对于提高自身的生存能力、突防能力、作战效能具有重要的理论价值和现实意义。围绕以上问题,本文在不确定环境下多UCAV实时任务规划问题方面进行了相关的理论研究,主要内容概括如下:首先,根据不确定环境下作战双方的态势,分析了决定任务分配结果的各项关键指标,如价值收益、毁伤代价、武器弹药代价、航程和燃油代价等,并充分考虑了这些指标中的不确定因素和不确定信息。其次,根据以上所分析的任务分配中的关键指标和指标中的不确定信息,考虑目标的动态特性,分别建立了随时间变化的系统数学优化模型和基于不确定信息的数学优化模型。最后,利用遗传算法、SMAA(Stochastic Multi-criteria Acceptability Analysis)方法及理想点法对数学优化模型进行动态求解,得到最优的任务分配结果。仿真结果验证了该模型和方法的有效性和适用性。在论文的最后,总结了本论文的研究成果,并指出了本论文研究的局限和对后续工作研究的建议。

【Abstract】 UCAV(Unmanned Combat Aerial Vehicle) can complete a variety of the complex combat tasks, and is playing more and more important role in morden war, so it attracts the attention of the national military. In the real battlefield environments, there are many uncertain factors such as the variability of the battlefield environment、the uncertainty of the acquired information、the randomness of the weapon’s damage effectiveness etc.Therefore, the problem of studying on the real-time task planning of multi-UCAV in uncertain environment is a new important topic. Moreover, task assignment is the guarantee and foundation of task planning system. Meanwhile, it has important theoretical value and realistic significance in improving the viability、penetration ability and combat effectiveness of UCAV. Around the above problems, the related theories about the problem of real-time task planning in uncertain environments are carried out in this paper, the main content can be summarized as follows:First, the key indexes which dccide the task assignment result are analyzed according to the combat situation in uncertain environment. For example, the target rewad, the damage cost, weapon and ammunition cost, the distance and fuel oil cost and so on. The uncertain facors and uncertain information in these indicators are fully considered. Secondly, according to the key indicators in task assignment and the uncertain information analyzed above, the mathematical optimization model with time-varying and the mathematical optimization model based on uncertain information are established which take the dynamia characteristics of the target into account. Lastly, the mathematical optimization models are solved using genetic algorithm, SMAA and ideal point method, the optimal task assignment result is obtained. The simulation results validate the applicability and effectiveness of the model and method.At last, the research fruits are summarized. Following that, the limitation of the research content and future research emphasis are pointed out.

【关键词】 UCAV任务规划不确定信息遗传算法SMAA
【Key words】 UCAVtask planninguncertain informationgenetic algorithmSMAA
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