摘要
提出了一类基于自适应神经模糊推理系统(ANFIS)的飞机驾驶员建模方法。首先建立了包含若干待定模糊规则参数的基本驾驶员Takagi-Sugeno模糊模型,将其转换成等效的ANFIS网络系统后,采用驾驶员实际操纵数据和自适应BP算法对模糊规则各个待定参数进行训练并建立最终的模型。进而对已建立的驾驶员模型进行人机闭环系统仿真,结果表明,较之传统的传递函数模型,ANFIS模型与驾驶员实际操作输出之间的拟合程度更加理想。
A method for building pilot models is proposed based on Adaptive Neural Fuzzy Inference System （ANFIS）. A basic Takagi-Sugeno fuzzy model of pilot is built at first, which contains several fuzzy-rule parameters to be determined. It is then transformed into the equivalent ANFIS network system. We use the actual flight data and the adaptive Back-Propagation（BP） algorithm to train the undetermined parameters of ANFIS, and obtained the final model. The simulation results of pilot-aircraft close - loop system showed that, comparing with the traditional transfer function methods, the ANFIS pilot model presented by our scheme is more reasonable and can illustrate the handling behavior more accurately.
出处
《电光与控制》
北大核心
2007年第5期102-105,116,共5页
Electronics Optics & Control
基金
国家自然科学基金(60174001)
北京市自然科学基金(4022007)
