Regression modelling technique for state model estimation and Kalman filter application

Manufacturing processes in which it is necessary to apply a Kalman filter algorithm to estimate the states associated with the process, because of the dynamic elements in the system that are not measurable, is considered. A method for applying the Kalman filter to processes by using a regression model of the output equation for the system is presented. This dynamical model can be applied to state estimation and filtering techniques for process qualification and other applications. An example is given to illustrate the method