Study on Identification Hammerstein Model of Transducer Based on Improved FLANN
LIU Tao1,HAN Hua-ting1,MA Jing2,LEI Chao1
1.Air Defense and Antimissile Institute, Air Force Engineering University, Xi’an, Shaanxi 710051, China;
2.Science and Technology on Information Assurance Laboratory, Beijing 100072, China
Abstract：For identification nonlinear dynamic model of transducer, a method for the nonlinear system one-stage identification by using functional link artificial neural network (FLANN) algorithm is proposed. The nonlinear system is described as a polynomial expression, combining the differential equation of dynamic system to build discrete data expression of input to output, solving the unknown parameters of the model by FLANN training. The convergence speed and the stability of convergence of FLANN algorithm is improved through variable learning factor. Experimental results show that the improved FLANN is simple and effective and has higher convergence rate.
刘滔,韩华亭,马婧,雷超. 基于函数连接神经网络的传感器Hammerstein模型辨识研究[J]. 计量学报, 2015, 36(1): 97-101.
LIU Tao,HAN Hua-ting,MA Jing,LEI Chao. Study on Identification Hammerstein Model of Transducer Based on Improved FLANN. Acta Metrologica Sinica, 2015, 36(1): 97-101.
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2015, Vol. 36 
