Apply Cross Spectral Analysis to Transfer Function Model Identification
Chang‐Jiang Zheng, Qifang Chen, Linbai Tong, Youxiang Cui · Advances in engineering research/Advances in Engineering Research · 2014
Transfer function models is of considerable interest in economics, engineering, biology, and many other fields.Models of this kind can describe not only the behavior of industrial processes but also that of economic and business systems.Transfer function model building is important because it is only when the dynamic characteristics of a system are understood that intelligent direction, manipulation, and control of the system is possible.Engineering methods for estimating transfer functions are usually based on the choice of special inputs to the system such as step and sine wave inputs and "pulse" inputs.These methods have been useful when the system is affected by small amounts of noise but are less satisfactory otherwise.In the presence of appreciable noise, it is necessary to use statistical methods for estimating the transfer function.In this paper we show that an alternative method for identifying transfer function models, which does not require prewhitening of the input, can be based on spectral analysis.Furthermore, it is easily generalized to multiple inputs.