基于进化式专家系统树的无人机空战决策技术

为解决传统专家系统方法无法应付非预期情况的问题，提出一种进化式的专家系统树方法来研究空战决策。以中距空战为例，建立2 维典型空战模型，将遗传算法和专家系统相结合，建立进化式专家系统树框架和战术决策系统，并在一对一空战场景下对所建立的方法进行仿真验证。仿真结果表明：该方法通过在多种战场设定下对决策规则的离线进化，使决策系统可根据战场情况做出调整，在己方飞行性能不占优势的情况下达成制胜目标。

UAV Air Combat Decision Based on Evolutionary Expert System Tree

For the problem that the traditional expert system method can not deal with the non-expecting situation,put forward the evolutionary expert system tree method to research on the air combat decision making problem. Takingmiddle range air combat as example, establish 2 dimension typical air combat model, combine the genetic method andexpert system, establish the evolutionary expert system tree frame and tactics decision making system. Simulate andverify it under 1 VS 1 air combat environment. The simulation results show that the method can carry out decisionmaking offline evolution under varied battlefield setting, the decision making system can adaptively make adjustingaccording to battlefield situation, and achieves the victory despite of a disadvantageous air speed setting in comparisonwith the opponent.