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基于规划目标图的无人机空战战术决策方法研究
王栋
Subtype工程硕士
Thesis Advisor常红星
2017-05
Degree Grantor中国科学院研究生院
Place of Conferral北京
Keyword规划目标图 Petri网 Cpn Tools 战术决策 Fpn
Abstract随着信息化技术和空战技术的快速发展,无人机编队协同空战有了更大的发展空间,由于无人机具备隐身和无人驾驶等特点,使得它能够代替人类执行一些高风险的作战任务,无人机编队空战技术的研究对未来空中战场的掌握具有重要的意义。
针对无人机编队空战问题,本文主要研究了空战过程中的战术决策方法,通过对规划目标图方法的研究,提出了空战任务的分解和表达方法,同时用Petri网和专家知识完成了规划目标图的推理过程,最后通过将空战的影响因子模糊化,借助模糊Petri网完成了战术决策的模糊推理。论文主要工作如下:
1. 研究规划目标图的模型,分析了规划目标图模型的树形结构和任务单元的构成方法,在此基础上提出了利用规划目标图模型来表达无人机编队空战中的任务知识,描述了使用PGG来描述空战任务时的分层次表达方法,将空战任务分为抽象任务和原子任务等,同时描述了在PGG中各个任务单元所包含的内容和构成方式,进而建立了使用PGG描述空战任务的表达模型。
2.提出了一种基于Petri网的规则推理方法来解决战术决策系统中的推理问题的方法。针对不同场景下,需要结合不同的战场态势和先验规则来进行战术推理,本文在总结了空战规则的基础上利用了Petri网建模工具CPN Tools实现了基于Petri网的规则推理系统模型设计,CPN Tools优秀的可视化效果和弱耦合性,帮助我们实现推理模型,能够直观的观察推理过程,并完成高效的模块化设计。
3.提出了使用基于模糊Petri网的推理算法来解决无人机编队战术决策的问题,将空战态势的影响因子利用隶属度函数进行模糊化处理,并为战术规则给出先验可信度,利用模糊逻辑和Petri网的优点,构建了基于FPN推理算法的战术决策模型,通过将仿真实验的结果与推理规则相对比,验证了该方法的准确性与有效性,同时提高了决策的连续性和智能化程度。
最后结合具体项目将上述无人机编队战术决策系统作为项目核心部分,验证了战术决策系统的有效性,通过实验结果发现战术决策系统能够对战场环境做出快速响应,并给出正确的决策指导。
Other AbstractWith the rapid development of information technology and air combat technology, cooperative air combat of UAV formation has a large space for development, due to the characteristics of UAV, such as unmanned, invisibility and etc., so it can replace human to do some high-risk tactical tasks, the research about the UAV formation air combat technology has a great meaning for grasping the future battlefield.
For the UAV formation air combat problem, this paper mainly focused on the method of tactical decision in air combat, through the research of the plan goal graph method, we proposed a decomposition and expression method of air combat tasks, at the same time, we finished the reasoning process of plan goal graph with using Petri net and expert knowledge, at the end, we finished the fuzzy reasoning of tactical decision with the using of fuzzy petri net and making the impact factor fuzzy. The main work of this paper is as follows:
1. This paper study on the plan goal graph, analyzes the method of tree structure and task unit of plan goal graph, puts forwards using plan goal graph to express mission knowledge in UAV formation combat, describes the hierarchical representation method when describe the combat task with PGG. The task of air combat mission is divided into abstract tasks and atomic tasks, the paper describes the content and composition of each task unit, the expression model of air combat mission using PGG is established then.
2. This paper proposes a rule-based reasoning method based on Petri nets to solve the inference problem in tactical decision system. For different scenarios, the tactics decision system need combine different battlefield situation and priori rules for tactical reasoning. In this paper, the petri net modeling tool CPN Tools is used to implement the rule inference system model based on the summary of air combat rules, the excellent visualization effect and weak coupling can help us to actualize the inference model, observe the inference process intuitively, and completes the highly effective modular design.
3. In this paper, a fuzzy Petri net based inference algorithm is proposed to solve the problem of UAV tactical decision making. The influence factors of air combat situation were treated by membership function, and give a priori credibility for each tactical rules, based on the advantages of fuzzy logic and Petri nets, a tactical decision model based on FPN inference algorithm is constructed. By comparing the simulation results with the reference rules, the accuracy and effectiveness of the proposed method are verified.
Finally, we use the tactical decision system we proposed as the core part of the specific projects, with the using of system in project, the effectiveness of tactical decision making system was verified, the experiment shows that the system can give the tactical result to the battlefield environment quickly, and gives the correct policy guidance.
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14716
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
王栋. 基于规划目标图的无人机空战战术决策方法研究[D]. 北京. 中国科学院研究生院,2017.
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