Abstract
Today's air combat has reached a high level of uncer-tainty where continuous or discrete variables with crisp values cannot be properly represented using fuzzy sets.With a set of membership functions,fuzzy logic is well-suited to tackle such complex states and actions.However,it is not necessary to fuzzify the variables that have definite discrete semantics.Hence,the aim of this study is to improve the level of model abstraction by proposing multiple levels of cascaded hierarchi-cal structures from the perspective of function,namely,the func-tional decision tree.This method is developed to represent behavioral modeling of air combat systems,and its metamodel,execution mechanism,and code generation can provide a sound basis for function-based behavioral modeling.As a proof of con-cept,an air combat simulation is developed to validate this method and the results show that the fighter Alpha built using the proposed framework provides better performance than that using default scripts.
基金项目
National Natural Science Foundation of China(62003359)
维普
万方数据