Survey on Nonlinear system Identification

System Identification is the method of constructing mathematical models from the observed data from a dynamic system. Mathematical modeling are playing an important role in today’s science and engineering for solving so many tasks such as simulation, controller design and proper signal processing. There are two important methods in modeling a system. First principle modeling, in which the physical knowledge of the system is used to obtain the model. When the prior knowledge about the measured data of the system are available the model may be derived from the measured data which is called Data driven model. In this paper we look onto to the pros and cons of traditional and modern way of system identification