Identification of wiener model of intelligence sensor based on hybrid neural networks

An identification method based on hybrid neural networks for Wiener model is investigated in this paper to analyze the nonlinear dynamic system of intelligence sensor, and the corresponding algorithm is presented. In this model, the nonlinear dynamic characteristic of sensor is expressed by cascading a linear dynamic subunit (LDS) with a nonlinear static subunit (NLSS). According to the characteristic of the model, an LDN linear neural network (LDN-LNN) simulating the LDS and a PID nonlinear neural network (PID-NLNN) simulating the NLSS form a hybrid neural network (HNN), which is used to identify Wiener model. By means of the HNN approach, the parameter of the model can be identified and separated into two parts simultaneously, one part is the coefficient of the LDS, the other is the coefficient of the NLSS. The simulation has proved the efficiency of the proposed method.