An Application of Random Process for Controlled Object Identification with Traffic Delay Problem

Abstract

Abstract:In the article proposed an effective method estimating transfer function model of controlled plant including dead-time delay, based on stochatstic time series of input-output signals. The model structure is modified with parameters optimized until the model error becomes "white-noise" series that with inough smal auto-correlation function. ProposeThe Real signals which occur in the control process always imlpy influences of many random factors, so the Directive Object Identification Problem is often related to random process. Mathematically, the Controlled Object Identification problem is the problem that predicts the trend of Random Process:-regressive function that reflects the trend of non-random process or is the model of the identification problem; ( ) u trandom error. The Theory of Prediction and Identification has been studied and developed with thousands of scientific works made public since last century. We can find the fundamental results of studies of statistics and prediction in [1,2], of kinetics system identification in detail in [3,4].To use linear algebra methods, we often try to change the regressive models into linear combination forms of coefficients: , to increase the model accuracy. With this approach, the object identification problem without dead time delay is considered to be completely solved in theory [1,4]. In fact, however, applying the pure polynomial