关键词: 无人作战飞机, 自主空战, 机动决策, 鲁棒多目标优化, 共生生物算法

Abstract: To solve the problem of Unmanned Combat Aerial Vehicles（UCAV） maneuvering decision during the automatic air combat, a new kind of robust maneuvering decision method is proposed. Firstly, robust membership functions that reflect the air combat situation are proposed in order to construct the Robust Multi-objective Optimization（RMO） functions. Then, in view of the incompleteness of maneuvering library and the timeliness limitation of traditional optimization method, a modified Symbiotic Organisms Search（SOS） algorithm which is based on adaptive and elite opposition-based learning strategy is used to optimize the control variables, so the maneuvering decision is completed. The simulation result shows that promising results can be obtained with the help of RMO, and the modified SOS has a better real-time performance which can satisfy the real-time requirement of maneuvering decision.

Key words: Unmanned Combat Aerial Vehicles（UCAV）, automatic air combat, maneuvering decision, Robust Multi-objective Optimization（RMO）, Symbiotic Organisms Search（SOS）