Research on nonlinear system identification based on input linearization dynamic recurrent neural network
Yun Du, Huiqin Sun, Fanhua Meng, Suying Zhang, Qiang Tian · 2010
In this paper, it studies the problems of the on-line identification on the nonlinear and time-lag SISO dynamic system. It puts forward the recurrent structure to linearize the input neurons of the neural network which can describe the feasibility of the algorithm, so the neural network has the dynamic on-line identification capability. Simulation results show that the input linearization dynamic recurrent network has a strong self-adaptability and robustness. It gives a new method for SISO nonlinear dynamic system identification.