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直升机控制系统的设计、飞行模拟器的研制及计算机实时仿真都离不开直升机数学模型 ,但是建立可靠而且准确的直升机飞行动力学模型是十分困难的 ,而且也很难保证动力学模型计算的快速性、可靠性与实时性。本文基于模糊推理技术 ,根据飞行试验数据辨识了直升机飞行模型 ,可以在一定程度上保证所辨识模型的简单、准确与计算的实时性。为了提高模糊模型的精度 ,文中采用了一种新方法来处理矛盾规则。本文利用模糊聚类分析的方法对海量的试验样本数据进行处理 ,有效地减少了辨识模型的规则数量。最后的仿真辨识结果表明 ,辨识效果合理 ,方法可行。
The design of helicopter control system, the development of flight simulator and the real-time simulation of the computer are all inseparable from the helicopter mathematical model, but it is very difficult to establish a reliable and accurate helicopter flight dynamics model, and it is difficult to ensure that the dynamic model calculation is fast Sex, reliability and real-time. Based on the fuzzy reasoning technology, this paper discerned the helicopter flight model based on the flight test data, which can ensure the simple, accurate and real-time calculation of the identified model to a certain extent. In order to improve the accuracy of the fuzzy model, a new method is adopted to deal with the conflict rules. In this paper, the method of fuzzy clustering analysis is used to process a large amount of experimental sample data, which effectively reduces the number of rules for identifying models. The final simulation identification results show that the identification effect is reasonable and the method is feasible.