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作 者:谭目来 丁达理 谢磊 丁维 吕丞辉 TAN Mulai;DING Dali;XIE Lei;DING Wei;LYU Chenghui(Aeronautics Engineering College,Air Force Engineering University,Xi’an 710038,China)
机构地区:[1]空军工程大学航空工程学院,陕西西安710038
出 处:《系统工程与电子技术》2022年第6期1984-1993,共10页Systems Engineering and Electronics
基 金:陕西省自然科学基金(2021JM-223,2020JQ-481)资助课题。
摘 要:针对现有研究中无人作战飞机(unmanned combat air vehicle,UCAV)近距逃逸机动的自适应性不足和战术性匮乏问题,提出一种将模糊专家系统与双策略竞争的可选外部存档差分进化算法(external archiving differential evolution algorithm with dual strategy competition,DSC-JADE)相结合的逃逸机动决策算法。通过对战术知识的学习,建立模糊专家系统,将逃逸决策过程通过滚动时域划分为离散片段,根据模糊专家系统决策得到机动动作,在其控制量对应的可行域内,采用改进差分进化算法(improved differential evolution,IDE)进行寻优得到最优控制量,完成逃逸机动决策。在UCAV处于劣势的初始条件下进行仿真验证,证明DSC-JADE算法相较原始差分进化以及其他传统群智能算法搜索能力更强,采用专家系统相较不采用专家系统逃逸决策能力更优。Aiming at the problems of insufficient adaptability and lack of tactical capabilities of unmanned combat air vehicle(UCAV)in short-range escape maneuvers in existing research,an escape maneuvering decision algorithm combining fuzzy expert system and external archiving differential evolution algorithm with dual strategy competition(DSC-JADE)is proposed.Through the learning of tactical knowledge,a fuzzy expert system is established,and the escape decision process is divided into discrete segments through the receding horizon.According to the decision of the fuzzy expert system,the maneuver is obtained.In the feasible region corresponding to its control quantity,an improved differential evolution(IDE)algorithm is used to search the optimal control quantity,and the escape maneuver decision is completed.Under the initial conditions of inferior(UCAV)for simulation and verification,the DSC-JADE algorithm has a stronger search ability than the differential evolution algorithm and other traditional group intelligence algorithms;the use of expert systems has better escape decision-making capabilities than the use of expert systems.
关 键 词:逃逸机动决策 模糊专家系统 改进差分进化算法 滚动时域控制
分 类 号:V279[航空宇航科学与技术—飞行器设计]
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