Identification of coaxial helicopter dynamic system with elman neural networks
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摘要: 根据共轴式直升机动力学与运动学基本方程的结构形式建立了一种基于改进的Elman神经网络的辨识模型,同时推导了该网络的训练算法,给出了训练步骤.随后,利用外场试飞中几个典型飞行状态的遥测数据对网络进行训练,计算权值矩阵,获得该共轴式直升机用来进行动力学系统分析的神经网络模型.以匀速前飞状态为例进行了纵向操纵响应仿真,比较仿真结果和实际遥测数据可知,该网络模型基本反映了样例机的动态特性.Abstract: A modified elman neural network according to the dynamic & kinematic equations of helicopters was established, the training algorithms for the neural networks(NN) was derived, and the training steps and their realizations were provided. From the telemetry data collection of real trial flights of a type of helicopter, the data of typical flying attitudes were exploited to train the NN and calculate the elements of associated weighted matrix, thus the NN for dynamic analysis against the helicopter was obtained. To illustrate the NN effeteness, the vertical operation response in the constant velocity forward flying attitude was simulated, comparing simulation results with real trial flight data shows that the NN basically reflects the real dynamic behavior of the helicopter.
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Key words:
- coaxial helicopter /
- dynamic model /
- neural networks /
- system identification
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[1] 周国仪.共轴式直升机飞行动力学建模及数值模拟 .北京:北京航空航天大学航空科学与工程学院,2003 Zhou Guoyi. Modeling and numerical simulation of thedynamics of coaxial helicopter . Beijing:School of Aeronautic Science and Engineering, Beijing University of Aeronautice and Astronautics, 2003(in Chines) [2] Hornik K, Stinchornbe M, White H. Multilayer feedforward network are universal approximators[J]. Neural Network,1989,2:359-366 [3] 阎平凡,张长水.人工神经网络与模拟进化计算[M].北京:清华大学出版社,2005:276-327 Yan Pingfan, Zhang Changshui. Artificial neural networks and evolutionary computing[M]. Beijig:Tshinghua University Press, 2005:276-327(in Chinese) [4] Williams R, Zipser D.A learning algorithm for continually running fully recurrent NN[J]. Neural Computation,1989,1:270-280 [5] Gernasky M. Simple recurrent network trained by RTRL and extended Kalmann filter algorithm[J]. Neural Network World, 2003, 13(3):223-234
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